Postgre SQL Quick Guide

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PostgreSQL - Quick GuidePostgreSQL - Quick Guide

PostgreSQL - Quick Guide

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PostgreSQL - OverviewPostgreSQL - Overview

PostgreSQL - Overview

PostgreSQL is a powerful, open source object-relational database system. It has more than

15 years of active development phase and a proven architecture that has earned it a

strong reputation for reliability, data integrity, and correctness.

This tutorial will give you a quick start with PostgreSQL and make you comfortable with

PostgreSQL programming.

PostgreSQL (pronounced as post-gress-Q-L) is an open source relational database

management system (DBMS) developed by a worldwide team of volunteers. PostgreSQL is

not controlled by any corporation or other private entity and the source code is available

free of charge.

PostgreSQL, originally called Postgres, was created at UCB by a computer science

professor named Michael Stonebraker. Stonebraker started Postgres in 1986 as a follow-up

project to its predecessor, Ingres, now owned by Computer Associates.

1977-1985 − A project called INGRES was developed.

Proof-of-concept for relational databases

Established the company Ingres in 1980

Bought by Computer Associates in 1994

1986-1994 − POSTGRES



What is PostgreSQL?What is PostgreSQL?

What is PostgreSQL?

A Brief History of PostgreSQLA Brief History of PostgreSQL

A Brief History of PostgreSQL



Development of the concepts in INGRES with a focus on object orientation

and the query language - Quel

The code base of INGRES was not used as a basis for POSTGRES

Commercialized as Illustra (bought by Informix, bought by IBM)

1994-1995 − Postgres95

Support for SQL was added in 1994

Released as Postgres95 in 1995

Re-released as PostgreSQL 6.0 in 1996

Establishment of the PostgreSQL Global Development Team

PostgreSQL runs on all major operating systems, including Linux, UNIX (AIX, BSD, HP-UX,

SGI IRIX, Mac OS X, Solaris, Tru64), and Windows. It supports text, images, sounds, and

video, and includes programming interfaces for C / C++, Java, Perl, Python, Ruby, Tcl and

Open Database Connectivity (ODBC).

PostgreSQL supports a large part of the SQL standard and offers many modern features

including the following −

Complex SQL queries

SQL Sub-selects

Foreign keys

Trigger

Views

Transactions

Multiversion concurrency control (MVCC)

Streaming Replication (as of 9.0)

Hot Standby (as of 9.0)

You can check official documentation of PostgreSQL to understand the above-mentioned

features. PostgreSQL can be extended by the user in many ways. For example by adding

new −

Data types

Functions

Operators

Aggregate functions

Key Features of PostgreSQLKey Features of PostgreSQL

Key Features of PostgreSQL

Index methods

PostgreSQL supports four standard procedural languages, which allows the users to write

their own code in any of the languages and it can be executed by PostgreSQL database

server. These procedural languages are - PL/pgSQL, PL/Tcl, PL/Perl and PL/Python.

Besides, other non-standard procedural languages like PL/PHP, PL/V8, PL/Ruby, PL/Java,

etc., are also supported.

PostgreSQL - Environment SetupPostgreSQL - Environment Setup

PostgreSQL - Environment Setup

To start understanding the PostgreSQL basics, first let us install the PostgreSQL. This

chapter explains about installing the PostgreSQL on Linux, Windows and Mac OS platforms.

Follow the given steps to install PostgreSQL on your Linux machine. Make sure you are

logged in as root before you proceed for the installation.

Pick the version number of PostgreSQL you want and, as exactly as possible, the

platform you want from EnterpriseDB

I downloaded postgresql-9.2.4-1-linux-x64.run for my 64 bit CentOS-6

machine. Now, let us execute it as follows −

[root@host]# chmod +x postgresql-9.2.4-1-linux-x64.run

[root@host]# ./postgresql-9.2.4-1-linux-x64.run

------------------------------------------------------------------------

Welcome to the PostgreSQL Setup Wizard.

------------------------------------------------------------------------

Please specify the directory where PostgreSQL will be installed.

Installation Directory [/opt/PostgreSQL/9.2]:

Once you launch the installer, it asks you a few basic questions like location of the

installation, password of the user who will use database, port number, etc. So keep

all of them at their default values except password, which you can provide

password as per your choice. It will install PostgreSQL at your Linux machine and

will display the following message −

Please wait while Setup installs PostgreSQL on your computer.

Installing

0% ______________ 50% ______________ 100%

#########################################

Procedural Languages SupportProcedural Languages Support

Procedural Languages Support

Installing PostgreSQL on Linux/UnixInstalling PostgreSQL on Linux/Unix

Installing PostgreSQL on Linux/Unix

-----------------------------------------------------------------------

Setup has finished installing PostgreSQL on your computer.

Follow the following post-installation steps to create your database −

[root@host]# su - postgres

Password:

bash-4.1$ createdb testdb

bash-4.1$ psql testdb

psql (8.4.13, server 9.2.4)

test=#

You can start/restart postgres server in case it is not running using the following

command −

[root@host]# service postgresql restart

Stopping postgresql service: [ OK ]

Starting postgresql service: [ OK ]

If your installation was correct, you will have PotsgreSQL prompt test=# as shown

above.

Follow the given steps to install PostgreSQL on your Windows machine. Make sure you

have turned Third Party Antivirus off while installing.

Pick the version number of PostgreSQL you want and, as exactly as possible, the

platform you want from EnterpriseDB

I downloaded postgresql-9.2.4-1-windows.exe for my Windows PC running in 32bit

mode, so let us run postgresql-9.2.4-1-windows.exe as administrator to install

PostgreSQL. Select the location where you want to install it. By default, it is

installed within Program Files folder.

Installing PostgreSQL on WindowsInstalling PostgreSQL on Windows

Installing PostgreSQL on Windows

The next step of the installation process would be to select the directory where

your data would be stored. By default, it is stored under the "data" directory.

Next, the setup asks for password, so you can use your favorite password.

The next step; keep the port as default.

In the next step, when asked for "Locale", I selected "English, United States".

It takes a while to install PostgreSQL on your system. On completion of the

installation process, you will get the following screen. Uncheck the checkbox and

click the Finish button.

After the installation process is completed, you can access pgAdmin III, StackBuilder and

PostgreSQL shell from your Program Menu under PostgreSQL 9.2.

Follow the given steps to install PostgreSQL on your Mac machine. Make sure you are

logged in as administrator before you proceed for the installation.

Pick the latest version number of PostgreSQL for Mac OS available at EnterpriseDB

I downloaded postgresql-9.2.4-1-osx.dmg for my Mac OS running with OS X

version 10.8.3. Now, let us open the dmg image in finder and just double click it

which will give you PostgreSQL installer in the following window −

Installing PostgreSQL on MacInstalling PostgreSQL on Mac

Installing PostgreSQL on Mac

Next, click the postgres-9.2.4-1-osx icon, which will give a warning message.

Accept the warning and proceed for further installation. It will ask for the

administrator password as seen in the following window −

Enter the password, proceed for the installation, and after this step, restart your Mac

machine. If you do not see the following window, start your installation once again.

Once you launch the installer, it asks you a few basic questions like location of the

installation, password of the user who will use database, port number etc.

Therefore, keep all of them at their default values except the password, which you

can provide as per your choice. It will install PostgreSQL in your Mac machine in

the Application folder which you can check −

Now, you can launch any of the program to start with. Let us start with SQL Shell.

When you launch SQL Shell, just use all the default values it displays except, enter

your password, which you had selected at the time of installation. If everything

goes fine, then you will be inside postgres database and a postgress# prompt will

be displayed as shown below −

Congratulations!!! Now you have your environment ready to start with PostgreSQL

database programming.

PostgreSQL - SyntaxPostgreSQL - Syntax

PostgreSQL - Syntax

This chapter provides a list of the PostgreSQL SQL commands, followed by the precise

syntax rules for each of these commands. This set of commands is taken from the psql

command-line tool. Now that you have Postgres installed, open the psql as −

Program Files → PostgreSQL 9.2 → SQL Shell(psql).

Using psql, you can generate a complete list of commands by using the \help command.

For the syntax of a specific command, use the following command −

postgres-# \help <command_name>

An SQL statement is comprised of tokens where each token can represent either a

keyword, identifier, quoted identifier, constant, or special character symbol. The table given

below uses a simple SELECT statement to illustrate a basic, but complete, SQL statement

and its components.

SELECT id, name FROM states

Token Type Keyword Identifiers Keyword Identifier

Description Command Id and name columns Clause Table name

The SQL StatementThe SQL Statement

The SQL Statement

Abort the current transaction.

ABORT [ WORK | TRANSACTION ]

Change the definition of an aggregate function.

ALTER AGGREGATE name ( type ) RENAME TO new_name

ALTER AGGREGATE name ( type ) OWNER TO new_owner

Change the definition of a conversion.

ALTER CONVERSION name RENAME TO new_name

ALTER CONVERSION name OWNER TO new_owner

Change a database specific parameter.

ALTER DATABASE name SET parameter { TO | = } { value | DEFAULT }

ALTER DATABASE name RESET parameter

ALTER DATABASE name RENAME TO new_name

ALTER DATABASE name OWNER TO new_owner

Change the definition of a domain specific parameter.

ALTER DOMAIN name { SET DEFAULT expression | DROP DEFAULT }

ALTER DOMAIN name { SET | DROP } NOT NULL

ALTER DOMAIN name ADD domain_constraint

ALTER DOMAIN name DROP CONSTRAINT constraint_name [ RESTRICT | CASCADE ]

ALTER DOMAIN name OWNER TO new_owner

Change the definition of a function.

ALTER FUNCTION name ( [ type [, ...] ] ) RENAME TO new_name

ALTER FUNCTION name ( [ type [, ...] ] ) OWNER TO new_owner

Change a user group.

PostgreSQL SQL commandsPostgreSQL SQL commands

PostgreSQL SQL commands

ABORTABORT

ABORT

ALTER AGGREGATEALTER AGGREGATE

ALTER AGGREGATE

ALTER CONVERSIONALTER CONVERSION

ALTER CONVERSION

ALTER DATABASEALTER DATABASE

ALTER DATABASE

ALTER DOMAINALTER DOMAIN

ALTER DOMAIN

ALTER FUNCTIONALTER FUNCTION

ALTER FUNCTION

ALTER GROUPALTER GROUP

ALTER GROUP

ALTER GROUP groupname ADD USER username [, ... ]

ALTER GROUP groupname DROP USER username [, ... ]

ALTER GROUP groupname RENAME TO new_name

Change the definition of an index.

ALTER INDEX name OWNER TO new_owner

ALTER INDEX name SET TABLESPACE indexspace_name

ALTER INDEX name RENAME TO new_name

Change the definition of a procedural language.

ALTER LANGUAGE name RENAME TO new_name

Change the definition of an operator.

ALTER OPERATOR name ( { lefttype | NONE }, { righttype | NONE } )

OWNER TO new_owner

Change the definition of an operator class.

ALTER OPERATOR CLASS name USING index_method RENAME TO new_name

ALTER OPERATOR CLASS name USING index_method OWNER TO new_owner

Change the definition of a schema.

ALTER SCHEMA name RENAME TO new_name

ALTER SCHEMA name OWNER TO new_owner

Change the definition of a sequence generator.

ALTER SEQUENCE name [ INCREMENT [ BY ] increment ]

[ MINVALUE minvalue | NO MINVALUE ]

[ MAXVALUE maxvalue | NO MAXVALUE ]

[ RESTART [ WITH ] start ] [ CACHE cache ] [ [ NO ] CYCLE ]

Change the definition of a table.

ALTER INDEXALTER INDEX

ALTER INDEX

ALTER LANGUAGEALTER LANGUAGE

ALTER LANGUAGE

ALTER OPERATORALTER OPERATOR

ALTER OPERATOR

ALTER OPERATOR CLASSALTER OPERATOR CLASS

ALTER OPERATOR CLASS

ALTER SCHEMAALTER SCHEMA

ALTER SCHEMA

ALTER SEQUENCEALTER SEQUENCE

ALTER SEQUENCE

ALTER TABLEALTER TABLE

ALTER TABLE

ALTER TABLE [ ONLY ] name [ * ]

action [, ... ]

ALTER TABLE [ ONLY ] name [ * ]

RENAME [ COLUMN ] column TO new_column

ALTER TABLE name

RENAME TO new_name

Where action is one of the following lines −

ADD [ COLUMN ] column_type [ column_constraint [ ... ] ]

DROP [ COLUMN ] column [ RESTRICT | CASCADE ]

ALTER [ COLUMN ] column TYPE type [ USING expression ]

ALTER [ COLUMN ] column SET DEFAULT expression

ALTER [ COLUMN ] column DROP DEFAULT

ALTER [ COLUMN ] column { SET | DROP } NOT NULL

ALTER [ COLUMN ] column SET STATISTICS integer

ALTER [ COLUMN ] column SET STORAGE { PLAIN | EXTERNAL | EXTENDED | MAIN }

ADD table_constraint

DROP CONSTRAINT constraint_name [ RESTRICT | CASCADE ]

CLUSTER ON index_name

SET WITHOUT CLUSTER

SET WITHOUT OIDS

OWNER TO new_owner

SET TABLESPACE tablespace_name

Change the definition of a tablespace.

ALTER TABLESPACE name RENAME TO new_name

ALTER TABLESPACE name OWNER TO new_owner

Change the definition of a trigger.

ALTER TRIGGER name ON table RENAME TO new_name

Change the definition of a type.

ALTER TYPE name OWNER TO new_owner

Change a database user account.

ALTER USER name [ [ WITH ] option [ ... ] ]

ALTER USER name RENAME TO new_name

ALTER USER name SET parameter { TO | = } { value | DEFAULT }

ALTER USER name RESET parameter

Where option can be −

ALTER TABLESPACEALTER TABLESPACE

ALTER TABLESPACE

ALTER TRIGGERALTER TRIGGER

ALTER TRIGGER

ALTER TYPEALTER TYPE

ALTER TYPE

ALTER USERALTER USER

ALTER USER

[ ENCRYPTED | UNENCRYPTED ] PASSWORD 'password'

| CREATEDB | NOCREATEDB

| CREATEUSER | NOCREATEUSER

| VALID UNTIL 'abstime'

Collect statistics about a database.

ANALYZE [ VERBOSE ] [ table [ (column [, ...] ) ] ]

Start a transaction block.

BEGIN [ WORK | TRANSACTION ] [ transaction_mode [, ...] ]

Where transaction_mode is one of −

ISOLATION LEVEL {

SERIALIZABLE | REPEATABLE READ | READ COMMITTED

| READ UNCOMMITTED

}

READ WRITE | READ ONLY

Force a transaction log checkpoint.

CHECKPOINT

Close a cursor.

CLOSE name

Cluster a table according to an index.

CLUSTER index_name ON table_name

CLUSTER table_name

CLUSTER

Define or change the comment of an object.

COMMENT ON {

TABLE object_name |

ANALYZEANALYZE

ANALYZE

BEGINBEGIN

BEGIN

CHECKPOINTCHECKPOINT

CHECKPOINT

CLOSECLOSE

CLUSTERCLUSTER

CLUSTER

COMMENTCOMMENT

COMMENT

COLUMN table_name.column_name |

AGGREGATE agg_name (agg_type) |

CAST (source_type AS target_type) |

CONSTRAINT constraint_name ON table_name |

CONVERSION object_name |

DATABASE object_name |

DOMAIN object_name |

FUNCTION func_name (arg1_type, arg2_type, ...) |

INDEX object_name |

LARGE OBJECT large_object_oid |

OPERATOR op (left_operand_type, right_operand_type) |

OPERATOR CLASS object_name USING index_method |

[ PROCEDURAL ] LANGUAGE object_name |

RULE rule_name ON table_name |

SCHEMA object_name |

SEQUENCE object_name |

TRIGGER trigger_name ON table_name |

TYPE object_name |

VIEW object_name

}

IS 'text'

Commit the current transaction.

COMMIT [ WORK | TRANSACTION ]

Copy data between a file and a table.

COPY table_name [ ( column [, ...] ) ]

FROM { 'filename' | STDIN }

[ WITH ]

[ BINARY ]

[ OIDS ]

[ DELIMITER [ AS ] 'delimiter' ]

[ NULL [ AS ] 'null string' ]

[ CSV [ QUOTE [ AS ] 'quote' ]

[ ESCAPE [ AS ] 'escape' ]

[ FORCE NOT NULL column [, ...] ]

COPY table_name [ ( column [, ...] ) ]

TO { 'filename' | STDOUT }

[ [ WITH ]

[ BINARY ]

[ OIDS ]

[ DELIMITER [ AS ] 'delimiter' ]

[ NULL [ AS ] 'null string' ]

[ CSV [ QUOTE [ AS ] 'quote' ]

[ ESCAPE [ AS ] 'escape' ]

[ FORCE QUOTE column [, ...] ]

Define a new aggregate function.

COMMITCOMMIT

COMMIT

COPYCOPY

COPY

CREATE AGGREGATECREATE AGGREGATE

CREATE AGGREGATE

CREATE AGGREGATE name (

BASETYPE = input_data_type,

SFUNC = sfunc,

STYPE = state_data_type

[, FINALFUNC = ffunc ]

[, INITCOND = initial_condition ]

)

Define a new cast.

CREATE CAST (source_type AS target_type)

WITH FUNCTION func_name (arg_types)

[ AS ASSIGNMENT | AS IMPLICIT ]

CREATE CAST (source_type AS target_type)

WITHOUT FUNCTION

[ AS ASSIGNMENT | AS IMPLICIT ]

Define a new constraint trigger.

CREATE CONSTRAINT TRIGGER name

AFTER events ON

table_name constraint attributes

FOR EACH ROW EXECUTE PROCEDURE func_name ( args )

Define a new conversion.

CREATE [DEFAULT] CONVERSION name

FOR source_encoding TO dest_encoding FROM func_name

Create a new database.

CREATE DATABASE name

[ [ WITH ] [ OWNER [=] db_owner ]

[ TEMPLATE [=] template ]

[ ENCODING [=] encoding ]

[ TABLESPACE [=] tablespace ]

]

Define a new domain.

CREATE DOMAIN name [AS] data_type

[ DEFAULT expression ]

[ constraint [ ... ] ]

CREATE CASTCREATE CAST

CREATE CAST

CREATE CONSTRAINT TRIGGERCREATE CONSTRAINT TRIGGER

CREATE CONSTRAINT TRIGGER

CREATE CONVERSIONCREATE CONVERSION

CREATE CONVERSION

CREATE DATABASECREATE DATABASE

CREATE DATABASE

CREATE DOMAINCREATE DOMAIN

CREATE DOMAIN

Where constraint is −

[ CONSTRAINT constraint_name ]

{ NOT NULL | NULL | CHECK (expression) }

Define a new function.

CREATE [ OR REPLACE ] FUNCTION name ( [ [ arg_name ] arg_type [, ...] ] )

RETURNS ret_type

{ LANGUAGE lang_name

| IMMUTABLE | STABLE | VOLATILE

| CALLED ON NULL INPUT | RETURNS NULL ON NULL INPUT | STRICT

| [ EXTERNAL ] SECURITY INVOKER | [ EXTERNAL ] SECURITY DEFINER

| AS 'definition'

| AS 'obj_file', 'link_symbol'

} ...

[ WITH ( attribute [, ...] ) ]

Define a new user group.

CREATE GROUP name [ [ WITH ] option [ ... ] ]

Where option can be:

SYSID gid

| USER username [, ...]

Define a new index.

CREATE [ UNIQUE ] INDEX name ON table [ USING method ]

( { column | ( expression ) } [ opclass ] [, ...] )

[ TABLESPACE tablespace ]

[ WHERE predicate ]

Define a new procedural language.

CREATE [ TRUSTED ] [ PROCEDURAL ] LANGUAGE name

HANDLER call_handler [ VALIDATOR val_function ]

Define a new operator.

CREATE OPERATOR name (

PROCEDURE = func_name

[, LEFTARG = left_type ] [, RIGHTARG = right_type ]

[, COMMUTATOR = com_op ] [, NEGATOR = neg_op ]

CREATE FUNCTIONCREATE FUNCTION

CREATE FUNCTION

CREATE GROUPCREATE GROUP

CREATE GROUP

CREATE INDEXCREATE INDEX

CREATE INDEX

CREATE LANGUAGECREATE LANGUAGE

CREATE LANGUAGE

CREATE OPERATORCREATE OPERATOR

CREATE OPERATOR

[, RESTRICT = res_proc ] [, JOIN = join_proc ]

[, HASHES ] [, MERGES ]

[, SORT1 = left_sort_op ] [, SORT2 = right_sort_op ]

[, LTCMP = less_than_op ] [, GTCMP = greater_than_op ]

)

Define a new operator class.

CREATE OPERATOR CLASS name [ DEFAULT ] FOR TYPE data_type

USING index_method AS

{ OPERATOR strategy_number operator_name [ ( op_type, op_type ) ] [ RECHECK ]

| FUNCTION support_number func_name ( argument_type [, ...] )

| STORAGE storage_type

} [, ... ]

Define a new rewrite rule.

CREATE [ OR REPLACE ] RULE name AS ON event

TO table [ WHERE condition ]

DO [ ALSO | INSTEAD ] { NOTHING | command | ( command ; command ... ) }

Define a new schema.

CREATE SCHEMA schema_name

[ AUTHORIZATION username ] [ schema_element [ ... ] ]

CREATE SCHEMA AUTHORIZATION username

[ schema_element [ ... ] ]

Define a new sequence generator.

CREATE [ TEMPORARY | TEMP ] SEQUENCE name

[ INCREMENT [ BY ] increment ]

[ MINVALUE minvalue | NO MINVALUE ]

[ MAXVALUE maxvalue | NO MAXVALUE ]

[ START [ WITH ] start ] [ CACHE cache ] [ [ NO ] CYCLE ]

Define a new table.

CREATE [ [ GLOBAL | LOCAL ] {

TEMPORARY | TEMP } ] TABLE table_name ( {

column_name data_type [ DEFAULT default_expr ] [ column_constraint [ ... ] ]

| table_constraint

| LIKE parent_table [ { INCLUDING | EXCLUDING } DEFAULTS ]

} [, ... ]

CREATE OPERATOR CLASSCREATE OPERATOR CLASS

CREATE OPERATOR CLASS

CREATE RULECREATE RULE

CREATE RULE

CREATE SCHEMACREATE SCHEMA

CREATE SCHEMA

CREATE SEQUENCECREATE SEQUENCE

CREATE SEQUENCE

CREATE TABLECREATE TABLE

CREATE TABLE

)

[ INHERITS ( parent_table [, ... ] ) ]

[ WITH OIDS | WITHOUT OIDS ]

[ ON COMMIT { PRESERVE ROWS | DELETE ROWS | DROP } ]

[ TABLESPACE tablespace ]

Where column_constraint is −

[ CONSTRAINT constraint_name ] {

NOT NULL |

NULL |

UNIQUE [ USING INDEX TABLESPACE tablespace ] |

PRIMARY KEY [ USING INDEX TABLESPACE tablespace ] |

CHECK (expression) |

REFERENCES ref_table [ ( ref_column ) ]

[ MATCH FULL | MATCH PARTIAL | MATCH SIMPLE ]

[ ON DELETE action ] [ ON UPDATE action ]

}

[ DEFERRABLE | NOT DEFERRABLE ] [ INITIALLY DEFERRED | INITIALLY IMMEDIATE ]

And table_constraint is −

[ CONSTRAINT constraint_name ]

{ UNIQUE ( column_name [, ... ] ) [ USING INDEX TABLESPACE tablespace ] |

PRIMARY KEY ( column_name [, ... ] ) [ USING INDEX TABLESPACE tablespace ] |

CHECK ( expression ) |

FOREIGN KEY ( column_name [, ... ] )

REFERENCES ref_table [ ( ref_column [, ... ] ) ]

[ MATCH FULL | MATCH PARTIAL | MATCH SIMPLE ]

[ ON DELETE action ] [ ON UPDATE action ] }

[ DEFERRABLE | NOT DEFERRABLE ] [ INITIALLY DEFERRED | INITIALLY IMMEDIATE ]

Define a new table from the results of a query.

CREATE [ [ GLOBAL | LOCAL ] { TEMPORARY | TEMP } ] TABLE table_name

[ (column_name [, ...] ) ] [ [ WITH | WITHOUT ] OIDS ]

AS query

Define a new tablespace.

CREATE TABLESPACE tablespace_name [ OWNER username ] LOCATION 'directory'

Define a new trigger.

CREATE TRIGGER name { BEFORE | AFTER } { event [ OR ... ] }

ON table [ FOR [ EACH ] { ROW | STATEMENT } ]

EXECUTE PROCEDURE func_name ( arguments )

CREATE TABLE ASCREATE TABLE AS

CREATE TABLE AS

CREATE TABLESPACECREATE TABLESPACE

CREATE TABLESPACE

CREATE TRIGGERCREATE TRIGGER

CREATE TRIGGER

Define a new data type.

CREATE TYPE name AS

( attribute_name data_type [, ... ] )

CREATE TYPE name (

INPUT = input_function,

OUTPUT = output_function

[, RECEIVE = receive_function ]

[, SEND = send_function ]

[, ANALYZE = analyze_function ]

[, INTERNALLENGTH = { internal_length | VARIABLE } ]

[, PASSEDBYVALUE ]

[, ALIGNMENT = alignment ]

[, STORAGE = storage ]

[, DEFAULT = default ]

[, ELEMENT = element ]

[, DELIMITER = delimiter ]

)

Define a new database user account.

CREATE USER name [ [ WITH ] option [ ... ] ]

Where option can be −

SYSID uid

| [ ENCRYPTED | UNENCRYPTED ] PASSWORD 'password'

| CREATEDB | NOCREATEDB

| CREATEUSER | NOCREATEUSER

| IN GROUP group_name [, ...]

| VALID UNTIL 'abs_time'

Define a new view.

CREATE [ OR REPLACE ] VIEW name [ ( column_name [, ...] ) ] AS query

Deallocate a prepared statement.

DEALLOCATE [ PREPARE ] plan_name

Define a cursor.

CREATE TYPECREATE TYPE

CREATE TYPE

CREATE USERCREATE USER

CREATE USER

CREATE VIEWCREATE VIEW

CREATE VIEW

DEALLOCATEDEALLOCATE

DEALLOCATE

DECLAREDECLARE

DECLARE

DECLARE name [ BINARY ] [ INSENSITIVE ] [ [ NO ] SCROLL ]

CURSOR [ { WITH | WITHOUT } HOLD ] FOR query

[ FOR { READ ONLY | UPDATE [ OF column [, ...] ] } ]

Delete rows of a table.

DELETE FROM [ ONLY ] table [ WHERE condition ]

Remove an aggregate function.

DROP AGGREGATE name ( type ) [ CASCADE | RESTRICT ]

Remove a cast.

DROP CAST (source_type AS target_type) [ CASCADE | RESTRICT ]

Remove a conversion.

DROP CONVERSION name [ CASCADE | RESTRICT ]

Remove a database.

DROP DATABASE name

Remove a domain.

DROP DOMAIN name [, ...] [ CASCADE | RESTRICT ]

Remove a function.

DROP FUNCTION name ( [ type [, ...] ] ) [ CASCADE | RESTRICT ]

Remove a user group.

DELETEDELETE

DELETE

DROP AGGREGATEDROP AGGREGATE

DROP AGGREGATE

DROP CASTDROP CAST

DROP CAST

DROP CONVERSIONDROP CONVERSION

DROP CONVERSION

DROP DATABASEDROP DATABASE

DROP DATABASE

DROP DOMAINDROP DOMAIN

DROP DOMAIN

DROP FUNCTIONDROP FUNCTION

DROP FUNCTION

DROP GROUPDROP GROUP

DROP GROUP

DROP GROUP name

Remove an index.

DROP INDEX name [, ...] [ CASCADE | RESTRICT ]

Remove a procedural language.

DROP [ PROCEDURAL ] LANGUAGE name [ CASCADE | RESTRICT ]

Remove an operator.

DROP OPERATOR name ( { left_type | NONE }, { right_type | NONE } )

[ CASCADE | RESTRICT ]

Remove an operator class.

DROP OPERATOR CLASS name USING index_method [ CASCADE | RESTRICT ]

Remove a rewrite rule.

DROP RULE name ON relation [ CASCADE | RESTRICT ]

Remove a schema.

DROP SCHEMA name [, ...] [ CASCADE | RESTRICT ]

Remove a sequence.

DROP SEQUENCE name [, ...] [ CASCADE | RESTRICT ]

Remove a table.

DROP TABLE name [, ...] [ CASCADE | RESTRICT ]

DROP INDEXDROP INDEX

DROP INDEX

DROP LANGUAGEDROP LANGUAGE

DROP LANGUAGE

DROP OPERATORDROP OPERATOR

DROP OPERATOR

DROP OPERATOR CLASSDROP OPERATOR CLASS

DROP OPERATOR CLASS

DROP RULEDROP RULE

DROP RULE

DROP SCHEMADROP SCHEMA

DROP SCHEMA

DROP SEQUENCEDROP SEQUENCE

DROP SEQUENCE

DROP TABLEDROP TABLE

DROP TABLE

Remove a tablespace.

DROP TABLESPACE tablespace_name

Remove a trigger.

DROP TRIGGER name ON table [ CASCADE | RESTRICT ]

Remove a data type.

DROP TYPE name [, ...] [ CASCADE | RESTRICT ]

Remove a database user account.

DROP USER name

Remove a view.

DROP VIEW name [, ...] [ CASCADE | RESTRICT ]

Commit the current transaction.

END [ WORK | TRANSACTION ]

Execute a prepared statement.

EXECUTE plan_name [ (parameter [, ...] ) ]

Show the execution plan of a statement.

EXPLAIN [ ANALYZE ] [ VERBOSE ] statement

DROP TABLESPACEDROP TABLESPACE

DROP TABLESPACE

DROP TRIGGERDROP TRIGGER

DROP TRIGGER

DROP TYPEDROP TYPE

DROP TYPE

DROP USERDROP USER

DROP USER

DROP VIEWDROP VIEW

DROP VIEW

ENDEND

END

EXECUTEEXECUTE

EXECUTE

EXPLAINEXPLAIN

EXPLAIN

Retrieve rows from a query using a cursor.

FETCH [ direction { FROM | IN } ] cursor_name

Where direction can be empty or one of −

PRIOR

FIRST

LAST

ABSOLUTE count

RELATIVE count

count

ALL

FORWARD

FORWARD count

FORWARD ALL

BACKWARD

BACKWARD count

BACKWARD ALL

Define access privileges.

GRANT { { SELECT | INSERT | UPDATE | DELETE | RULE | REFERENCES | TRIGGER }

[,...] | ALL [ PRIVILEGES ] }

ON [ TABLE ] table_name [, ...]

TO { username | GROUP group_name | PUBLIC } [, ...] [ WITH GRANT OPTION ]

GRANT { { CREATE | TEMPORARY | TEMP } [,...] | ALL [ PRIVILEGES ] }

ON DATABASE db_name [, ...]

TO { username | GROUP group_name | PUBLIC } [, ...] [ WITH GRANT OPTION ]

GRANT { CREATE | ALL [ PRIVILEGES ] }

ON TABLESPACE tablespace_name [, ...]

TO { username | GROUP group_name | PUBLIC } [, ...] [ WITH GRANT OPTION ]

GRANT { EXECUTE | ALL [ PRIVILEGES ] }

ON FUNCTION func_name ([type, ...]) [, ...]

TO { username | GROUP group_name | PUBLIC } [, ...] [ WITH GRANT OPTION ]

GRANT { USAGE | ALL [ PRIVILEGES ] }

ON LANGUAGE lang_name [, ...]

TO { username | GROUP group_name | PUBLIC } [, ...] [ WITH GRANT OPTION ]

GRANT { { CREATE | USAGE } [,...] | ALL [ PRIVILEGES ] }

ON SCHEMA schema_name [, ...]

TO { username | GROUP group_name | PUBLIC } [, ...] [ WITH GRANT OPTION ]

Create new rows in a table.

FETCHFETCH

FETCH

GRANTGRANT

GRANT

INSERTINSERT

INSERT

INSERT INTO table [ ( column [, ...] ) ]

{ DEFAULT VALUES | VALUES ( { expression | DEFAULT } [, ...] ) | query }

Listen for a notification.

LISTEN name

Load or reload a shared library file.

LOAD 'filename'

Lock a table.

LOCK [ TABLE ] name [, ...] [ IN lock_mode MODE ] [ NOWAIT ]

Where lock_mode is one of −

ACCESS SHARE | ROW SHARE | ROW EXCLUSIVE | SHARE UPDATE EXCLUSIVE

| SHARE | SHARE ROW EXCLUSIVE | EXCLUSIVE | ACCESS EXCLUSIVE

Position a cursor.

MOVE [ direction { FROM | IN } ] cursor_name

Generate a notification.

NOTIFY name

Prepare a statement for execution.

PREPARE plan_name [ (data_type [, ...] ) ] AS statement

Rebuild indexes.

REINDEX { DATABASE | TABLE | INDEX } name [ FORCE ]

LISTENLISTEN

LISTEN

LOADLOAD

LOAD

LOCKLOCK

LOCK

MOVEMOVE

MOVE

NOTIFYNOTIFY

NOTIFY

PREPAREPREPARE

PREPARE

REINDEXREINDEX

REINDEX

Destroy a previously defined savepoint.

RELEASE [ SAVEPOINT ] savepoint_name

Restore the value of a runtime parameter to the default value.

RESET name

RESET ALL

Remove access privileges.

REVOKE [ GRANT OPTION FOR ]

{ { SELECT | INSERT | UPDATE | DELETE | RULE | REFERENCES | TRIGGER }

[,...] | ALL [ PRIVILEGES ] }

ON [ TABLE ] table_name [, ...]

FROM { username | GROUP group_name | PUBLIC } [, ...]

[ CASCADE | RESTRICT ]

REVOKE [ GRANT OPTION FOR ]

{ { CREATE | TEMPORARY | TEMP } [,...] | ALL [ PRIVILEGES ] }

ON DATABASE db_name [, ...]

FROM { username | GROUP group_name | PUBLIC } [, ...]

[ CASCADE | RESTRICT ]

REVOKE [ GRANT OPTION FOR ]

{ CREATE | ALL [ PRIVILEGES ] }

ON TABLESPACE tablespace_name [, ...]

FROM { username | GROUP group_name | PUBLIC } [, ...]

[ CASCADE | RESTRICT ]

REVOKE [ GRANT OPTION FOR ]

{ EXECUTE | ALL [ PRIVILEGES ] }

ON FUNCTION func_name ([type, ...]) [, ...]

FROM { username | GROUP group_name | PUBLIC } [, ...]

[ CASCADE | RESTRICT ]

REVOKE [ GRANT OPTION FOR ]

{ USAGE | ALL [ PRIVILEGES ] }

ON LANGUAGE lang_name [, ...]

FROM { username | GROUP group_name | PUBLIC } [, ...]

[ CASCADE | RESTRICT ]

REVOKE [ GRANT OPTION FOR ]

{ { CREATE | USAGE } [,...] | ALL [ PRIVILEGES ] }

ON SCHEMA schema_name [, ...]

FROM { username | GROUP group_name | PUBLIC } [, ...]

[ CASCADE | RESTRICT ]

RELEASE SAVEPOINTRELEASE SAVEPOINT

RELEASE SAVEPOINT

RESETRESET

RESET

REVOKEREVOKE

REVOKE

ROLLBACKROLLBACK

ROLLBACK

Abort the current transaction.

ROLLBACK [ WORK | TRANSACTION ]

Roll back to a savepoint.

ROLLBACK [ WORK | TRANSACTION ] TO [ SAVEPOINT ] savepoint_name

Define a new savepoint within the current transaction.

SAVEPOINT savepoint_name

Retrieve rows from a table or view.

SELECT [ ALL | DISTINCT [ ON ( expression [, ...] ) ] ]

* | expression [ AS output_name ] [, ...]

[ FROM from_item [, ...] ]

[ WHERE condition ]

[ GROUP BY expression [, ...] ]

[ HAVING condition [, ...] ]

[ { UNION | INTERSECT | EXCEPT } [ ALL ] select ]

[ ORDER BY expression [ ASC | DESC | USING operator ] [, ...] ]

[ LIMIT { count | ALL } ]

[ OFFSET start ]

[ FOR UPDATE [ OF table_name [, ...] ] ]

Where from_item can be one of:

[ ONLY ] table_name [ * ] [ [ AS ] alias [ ( column_alias [, ...] ) ] ]

( select ) [ AS ] alias [ ( column_alias [, ...] ) ]

function_name ( [ argument [, ...] ] )

[ AS ] alias [ ( column_alias [, ...] | column_definition [, ...] ) ]

function_name ( [ argument [, ...] ] ) AS ( column_definition [, ...] )

from_item [ NATURAL ] join_type from_item

[ ON join_condition | USING ( join_column [, ...] ) ]

Define a new table from the results of a query.

SELECT [ ALL | DISTINCT [ ON ( expression [, ...] ) ] ]

* | expression [ AS output_name ] [, ...]

INTO [ TEMPORARY | TEMP ] [ TABLE ] new_table

[ FROM from_item [, ...] ]

[ WHERE condition ]

[ GROUP BY expression [, ...] ]

[ HAVING condition [, ...] ]

[ { UNION | INTERSECT | EXCEPT } [ ALL ] select ]

ROLLBACK TO SAVEPOINTROLLBACK TO SAVEPOINT

ROLLBACK TO SAVEPOINT

SAVEPOINTSAVEPOINT

SAVEPOINT

SELECTSELECT

SELECT

SELECT INTOSELECT INTO

SELECT INTO

[ ORDER BY expression [ ASC | DESC | USING operator ] [, ...] ]

[ LIMIT { count | ALL } ]

[ OFFSET start ]

[ FOR UPDATE [ OF table_name [, ...] ] ]

Change a runtime parameter.

SET [ SESSION | LOCAL ] name { TO | = } { value | 'value' | DEFAULT }

SET [ SESSION | LOCAL ] TIME ZONE { time_zone | LOCAL | DEFAULT }

Set constraint checking modes for the current transaction.

SET CONSTRAINTS { ALL | name [, ...] } { DEFERRED | IMMEDIATE }

Set the session user identifier and the current user identifier of the current session.

SET [ SESSION | LOCAL ] SESSION AUTHORIZATION username

SET [ SESSION | LOCAL ] SESSION AUTHORIZATION DEFAULT

RESET SESSION AUTHORIZATION

Set the characteristics of the current transaction.

SET TRANSACTION transaction_mode [, ...]

SET SESSION CHARACTERISTICS AS TRANSACTION transaction_mode [, ...]

Where transaction_mode is one of −

ISOLATION LEVEL { SERIALIZABLE | REPEATABLE READ | READ COMMITTED

| READ UNCOMMITTED }

READ WRITE | READ ONLY

Show the value of a runtime parameter.

SHOW name

SHOW ALL

Start a transaction block.

START TRANSACTION [ transaction_mode [, ...] ]

SETSET

SET

SET CONSTRAINTSSET CONSTRAINTS

SET CONSTRAINTS

SET SESSION AUTHORIZATIONSET SESSION AUTHORIZATION

SET SESSION AUTHORIZATION

SET TRANSACTIONSET TRANSACTION

SET TRANSACTION

SHOWSHOW

SHOW

START TRANSACTIONSTART TRANSACTION

START TRANSACTION

Where transaction_mode is one of −

ISOLATION LEVEL { SERIALIZABLE | REPEATABLE READ | READ COMMITTED

| READ UNCOMMITTED }

READ WRITE | READ ONLY

Empty a table.

TRUNCATE [ TABLE ] name

Stop listening for a notification.

UNLISTEN { name | * }

Update rows of a table.

UPDATE [ ONLY ] table SET column = { expression | DEFAULT } [, ...]

[ FROM from_list ]

[ WHERE condition ]

Garbage-collect and optionally analyze a database.

VACUUM [ FULL ] [ FREEZE ] [ VERBOSE ] [ table ]

VACUUM [ FULL ] [ FREEZE ] [ VERBOSE ] ANALYZE [ table [ (column [, ...] ) ] ]

PostgreSQL - Data TypePostgreSQL - Data Type

PostgreSQL - Data Type

In this chapter, we will discuss about the data types used in PostgreSQL. While creating

table, for each column, you specify a data type, i.e., what kind of data you want to store in

the table fields.

This enables several benefits −

Consistency − Operations against columns of same data type give consistent

results and are usually the fastest.

Validation − Proper use of data types implies format validation of data and

rejection of data outside the scope of data type.

Compactness − As a column can store a single type of value, it is stored in a

compact way.

TRUNCATETRUNCATE

TRUNCATE

UNLISTENUNLISTEN

UNLISTEN

UPDATEUPDATE

UPDATE

VACUUMVACUUM

VACUUM

Performance − Proper use of data types gives the most efficient storage of data.

The values stored can be processed quickly, which enhances the performance.

PostgreSQL supports a wide set of Data Types. Besides, users can create their own custom

data type using CREATE TYPE SQL command. There are different categories of data types

in PostgreSQL. They are discussed below.

Numeric types consist of two-byte, four-byte, and eight-byte integers, four-byte and eight-

byte floating-point numbers, and selectable-precision decimals. The following table lists

the available types.

Name Storage Size Description Range

smallint 2 bytes small-range

integer -32768 to +32767

integer 4 bytes typical choice for

integer -2147483648 to +2147483647

bigint 8 bytes large-range

integer

-9223372036854775808 to

9223372036854775807

decimal variable user-specified

precision,exact

up to 131072 digits before the decimal

point; up to 16383 digits after the decimal

point

numeric variable user-specified

precision,exact

up to 131072 digits before the decimal

point; up to 16383 digits after the decimal

point

real 4 bytes variable-

precision,inexact 6 decimal digits precision

double

precision 8 bytes variable-

precision,inexact 15 decimal digits precision

smallserial 2 bytes

small

autoincrementing

integer

1 to 32767

serial 4 bytes autoincrementing

integer 1 to 2147483647

bigserial 8 bytes

large

autoincrementing

integer

1 to 9223372036854775807

Numeric TypesNumeric Types

Numeric Types

The money type stores a currency amount with a fixed fractional precision. Values of the

numeric, int, and bigint data types can be cast to money. Using Floating point numbers is

not recommended to handle money due to the potential for rounding errors.

Name Storage Size Description Range

money 8 bytes currency

amount

-92233720368547758.08 to

+92233720368547758.07

The table given below lists the general-purpose character types available in PostgreSQL.

S. No. Name & Description

character varying(n), varchar(n)

variable-length with limit

character(n), char(n)

fixed-length, blank padded

text

variable unlimited length

The bytea data type allows storage of binary strings as in the table given below.

Name Storage Size Description

bytea 1 or 4 bytes plus the actual binary string variable-length binary string

PostgreSQL supports a full set of SQL date and time types, as shown in table below. Dates

are counted according to the Gregorian calendar. Here, all the types have resolution of 1

microsecond / 14 digits except date type, whose resolution is day.

Monetary TypesMonetary Types

Monetary Types

Character TypesCharacter Types

Character Types

Binary Data TypesBinary Data Types

Binary Data Types

Date/Time TypesDate/Time Types

Date/Time Types

Name Storage Size Description Low Value High Value

timestamp [(p)]

[without time

zone ]

8 bytes

both date and

time (no time

zone)

4713 BC 294276 AD

timestamp [(p) ]

with time zone 8 bytes

both date and

time, with time

zone

4713 BC 294276 AD

date 4 bytes date (no time of

day) 4713 BC 5874897 AD

time [ (p)] [

without time zone

]

8 bytes time of day (no

date) 00:00:00 24:00:00

time [ (p)] with

time zone 12 bytes times of day only,

with time zone 00:00:00+1459 24:00:00-1459

interval [fields ]

[(p) ] 12 bytes time interval -178000000

years

178000000

years

PostgreSQL provides the standard SQL type Boolean. The Boolean data type can have the

states true, false, and a third state, unknown, which is represented by the SQL null value.

Name Storage Size Description

boolean 1 byte state of true or false

Enumerated (enum) types are data types that comprise a static, ordered set of values.

They are equivalent to the enum types supported in a number of programming languages.

Unlike other types, Enumerated Types need to be created using CREATE TYPE command.

This type is used to store a static, ordered set of values. For example compass directions,

i.e., NORTH, SOUTH, EAST, and WEST or days of the week as shown below −

CREATE TYPE week AS ENUM ('Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun');

Enumerated, once created, can be used like any other types.

Boolean TypeBoolean Type

Boolean Type

Enumerated TypeEnumerated Type

Enumerated Type

Geometric TypeGeometric Type

Geometric Type

Geometric data types represent two-dimensional spatial objects. The most fundamental

type, the point, forms the basis for all of the other types.

Name Storage Size Representation Description

point 16 bytes Point on a plane (x,y)

line 32 bytes Infinite line (not fully

implemented)

((x1,y1),(x2,y2))

lseg 32 bytes Finite line segment ((x1,y1),(x2,y2))

box 32 bytes Rectangular box ((x1,y1),(x2,y2))

path 16+16n bytes Closed path (similar to

polygon) ((x1,y1),...)

path 16+16n bytes Open path [(x1,y1),...]

polygon 40+16n Polygon (similar to closed path) ((x1,y1),...)

circle 24 bytes Circle <(x,y),r> (center point and

radius)

PostgreSQL offers data types to store IPv4, IPv6, and MAC addresses. It is better to use

these types instead of plain text types to store network addresses, because these types

offer input error checking and specialized operators and functions.

Name Storage Size Description

cidr 7 or 19 bytes IPv4 and IPv6 networks

inet 7 or 19 bytes IPv4 and IPv6 hosts and networks

macaddr 6 bytes MAC addresses

Bit String Types are used to store bit masks. They are either 0 or 1. There are two SQL bit

types: bit(n) and bit varying(n), where n is a positive integer.

Network Address TypeNetwork Address Type

Network Address Type

Bit String TypeBit String Type

Bit String Type

Text Search TypeText Search Type

Text Search Type

This type supports full text search, which is the activity of searching through a collection of

natural-language documents to locate those that best match a query. There are two Data

Types for this −

S. No. Name & Description

tsvector

This is a sorted list of distinct words that have been normalized to merge

different variants of the same word, called as "lexemes".

tsquery

This stores lexemes that are to be searched for, and combines them honoring

the Boolean operators & (AND), | (OR), and ! (NOT). Parentheses can be used

to enforce grouping of the operators.

A UUID (Universally Unique Identifiers) is written as a sequence of lower-case hexadecimal

digits, in several groups separated by hyphens, specifically a group of eight digits, followed

by three groups of four digits, followed by a group of 12 digits, for a total of 32 digits

representing the 128 bits.

An example of a UUID is − 550e8400-e29b-41d4-a716-446655440000

The XML data type can be used to store XML data. For storing XML data, first you have to

create XML values using the function xmlparse as follows −

XMLPARSE (DOCUMENT '<?xml version="1.0"?>

<title>PostgreSQL Tutorial </title>

</tutorial>')

XMLPARSE (CONTENT 'xyz<foo>bar</foo><bar>foo</bar>')

The json data type can be used to store JSON (JavaScript Object Notation) data. Such data

can also be stored as text, but the json data type has the advantage of checking that each

stored value is a valid JSON value. There are also related support functions available,

which can be used directly to handle JSON data type as follows.

UUID TypeUUID Type

UUID Type

XML TypeXML Type

XML Type

JSON TypeJSON Type

JSON Type

Example Example Result

array_to_json('{{1,5},{99,100}}'::int[]) [[1,5],[99,100]]

row_to_json(row(1,'foo')) {"f1":1,"f2":"foo"}

PostgreSQL gives the opportunity to define a column of a table as a variable length

multidimensional array. Arrays of any built-in or user-defined base type, enum type, or

composite type can be created.

Array type can be declared as

CREATE TABLE monthly_savings (

name text,

saving_per_quarter integer[],

scheme text[][]

);

or by using the keyword "ARRAY" as

CREATE TABLE monthly_savings (

name text,

saving_per_quarter integer ARRAY[4],

scheme text[][]

);

Array values can be inserted as a literal constant, enclosing the element values within curly

braces and separating them by commas. An example is shown below −

INSERT INTO monthly_savings

VALUES (‘Manisha’,

‘{20000, 14600, 23500, 13250}’,

‘{{“FD”, “MF”}, {“FD”, “Property”}}’);

An example for accessing Arrays is shown below. The command given below will select the

persons whose savings are more in second quarter than fourth quarter.

SELECT name FROM monhly_savings WHERE saving_per_quarter[2] > saving_per_quarter[4];

An example of modifying arrays is as shown below.

Array TypeArray Type

Array Type

Declaration of ArraysDeclaration of Arrays

Declaration of Arrays

Inserting valuesInserting values

Inserting values

Accessing ArraysAccessing Arrays

Accessing Arrays

Modifying ArraysModifying Arrays

Modifying Arrays

UPDATE monthly_savings SET saving_per_quarter = '{25000,25000,27000,27000}'

WHERE name = 'Manisha';

or using the ARRAY expression syntax −

UPDATE monthly_savings SET saving_per_quarter = ARRAY[25000,25000,27000,27000]

WHERE name = 'Manisha';

An example of searching arrays is as shown below.

SELECT * FROM monthly_savings WHERE saving_per_quarter[1] = 10000 OR

saving_per_quarter[2] = 10000 OR

saving_per_quarter[3] = 10000 OR

saving_per_quarter[4] = 10000;

If the size of array is known, the search method given above can be used. Else, the

following example shows how to search when the size is not known.

SELECT * FROM monthly_savings WHERE 10000 = ANY (saving_per_quarter);

This type represents a list of field names and their data types, i.e., structure of a row or

record of a table.

The following example shows how to declare a composite type

CREATE TYPE inventory_item AS (

name text,

supplier_id integer,

price numeric

);

This data type can be used in the create tables as below −

CREATE TABLE on_hand (

item inventory_item,

count integer

);

Composite values can be inserted as a literal constant, enclosing the field values within

parentheses and separating them by commas. An example is shown below −

INSERT INTO on_hand VALUES (ROW('fuzzy dice', 42, 1.99), 1000);

Searching ArraysSearching Arrays

Searching Arrays

Composite TypesComposite Types

Composite Types

Declaration of Composite TypesDeclaration of Composite Types

Declaration of Composite Types

Composite Value InputComposite Value Input

Composite Value Input

This is valid for the inventory_item defined above. The ROW keyword is actually optional

as long as you have more than one field in the expression.

To access a field of a composite column, use a dot followed by the field name, much like

selecting a field from a table name. For example, to select some subfields from our

on_hand example table, the query would be as shown below −

SELECT (item).name FROM on_hand WHERE (item).price > 9.99;

You can even use the table name as well (for instance in a multitable query), like this −

SELECT (on_hand.item).name FROM on_hand WHERE (on_hand.item).price > 9.99;

Range types represent data types that uses a range of data. Range type can be discrete

ranges (e.g., all integer values 1 to 10) or continuous ranges (e.g., any point in time

between 10:00am and 11:00am).

The built-in range types available include the following ranges −

int4range − Range of integer

int8range − Range of bigint

numrange − Range of numeric

tsrange − Range of timestamp without time zone

tstzrange − Range of timestamp with time zone

daterange − Range of date

Custom range types can be created to make new types of ranges available, such as IP

address ranges using the inet type as a base, or float ranges using the float data type as a

base.

Range types support inclusive and exclusive range boundaries using the [ ] and ( )

characters, respectively. For example '[4,9)' represents all the integers starting from and

including 4 up to but not including 9.

Object identifiers (OIDs) are used internally by PostgreSQL as primary keys for various

system tables. If WITH OIDS is specified or default_with_oids configuration variable is

enabled, only then, in such cases OIDs are added to user-created tables. The following

Accessing Composite TypesAccessing Composite Types

Accessing Composite Types

Range TypesRange Types

Range Types

Object Identifier TypesObject Identifier Types

Object Identifier Types

table lists several alias types. The OID alias types have no operations of their own except

for specialized input and output routines.

Name References Description Value Example

oid any numeric object identifier 564182

regproc pg_proc function name sum

regprocedure pg_proc function with argument

types sum(int4)

regoper pg_operator operator name +

regoperator pg_operator operator with argument

types

*(integer,integer) or -

(NONE,integer)

regclass pg_class relation name pg_type

regtype pg_type data type name integer

regconfig pg_ts_config text search configuration English

regdictionary pg_ts_dict text search dictionary simple

The PostgreSQL type system contains a number of special-purpose entries that are

collectively called pseudo-types. A pseudo-type cannot be used as a column data type, but

it can be used to declare a function's argument or result type.

The table given below lists the existing pseudo-types.

S. No. Name & Description

any

Indicates that a function accepts any input data type.

anyelement

Indicates that a function accepts any data type.

anyarray

Indicates that a function accepts any array data type.

4anynonarray

Pseudo TypesPseudo Types

Pseudo Types

Indicates that a function accepts any non-array data type.

anyenum

Indicates that a function accepts any enum data type.

anyrange

Indicates that a function accepts any range data type.

cstring

Indicates that a function accepts or returns a null-terminated C string.

internal

Indicates that a function accepts or returns a server-internal data type.

language_handler

A procedural language call handler is declared to return language_handler.

fdw_handler

A foreign-data wrapper handler is declared to return fdw_handler.

record

Identifies a function returning an unspecified row type.

trigger

A trigger function is declared to return trigger.

void

Indicates that a function returns no value.

PostgreSQL - CREATE DatabasePostgreSQL - CREATE Database

PostgreSQL - CREATE Database

This chapter discusses about how to create a new database in your PostgreSQL.

PostgreSQL provides two ways of creating a new database −

Using CREATE DATABASE, an SQL command.

Using createdb a command-line executable.

This command will create a database from PostgreSQL shell prompt, but you should have

appropriate privilege to create a database. By default, the new database will be created by

cloning the standard system database template1.

The basic syntax of CREATE DATABASE statement is as follows −

CREATE DATABASE dbname;

where dbname is the name of a database to create.

The following is a simple example, which will create testdb in your PostgreSQL schema

postgres=# CREATE DATABASE testdb;

postgres-#

PostgreSQL command line executable createdb is a wrapper around the SQL command

CREATE DATABASE. The only difference between this command and SQL command

CREATE DATABASE is that the former can be directly run from the command line and it

allows a comment to be added into the database, all in one command.

The syntax for createdb is as shown below −

createdb [option...] [dbname [description]]

The table given below lists the parameters with their descriptions.

S. No. Parameter & Description

dbname

The name of a database to create.

description

Specifies a comment to be associated with the newly created database.

3options

Using CREATE DATABASEUsing CREATE DATABASE

Using CREATE DATABASE

SyntaxSyntax

Syntax

ExampleExample

Example

Using createdb CommandUsing createdb Command

Using createdb Command

SyntaxSyntax

Syntax

ParametersParameters

Parameters

command-line arguments, which createdb accepts.

The following table lists the command line arguments createdb accepts −

S. No. Option & Description

-D tablespace

Specifies the default tablespace for the database.

-e

Echo the commands that createdb generates and sends to the server.

-E encoding

Specifies the character encoding scheme to be used in this database.

-l locale

Specifies the locale to be used in this database.

-T template

Specifies the template database from which to build this database.

--help

Show help about createdb command line arguments, and exit.

-h host

Specifies the host name of the machine on which the server is running.

-p port

Specifies the TCP port or the local Unix domain socket file extension on which

the server is listening for connections.

-U username

User name to connect as.

10 -w

OptionsOptions

Options

Never issue a password prompt.

-W

Force createdb to prompt for a password before connecting to a database.

Open the command prompt and go to the directory where PostgreSQL is installed. Go to

the bin directory and execute the following command to create a database.

createdb -h localhost -p 5432 -U postgres testdb

password ******

The above given command will prompt you for password of the PostgreSQL admin user,

which is postgres, by default. Hence, provide a password and proceed to create your new

database

Once a database is created using either of the above-mentioned methods, you can check it

in the list of databases using \l, i.e., backslash el command as follows −

postgres-# \l

List of databases

-----------+----------+----------+---------+-------+-----------------------

postgres | postgres | UTF8 | C | C |

template0 | postgres | UTF8 | C | C | =c/postgres +

template1 | postgres | UTF8 | C | C | =c/postgres +

testdb | postgres | UTF8 | C | C |

(4 rows)

postgres-#

PostgreSQL - SELECT DatabasePostgreSQL - SELECT Database

PostgreSQL - SELECT Database

This chapter explains various methods of accessing the database. Assume that we have

already created a database in our previous chapter. You can select the database using

either of the following methods −

Database SQL Prompt

OS Command Prompt

Assume you have already launched your PostgreSQL client and you have landed at the

following SQL prompt −

postgres=#

Database SQL PromptDatabase SQL Prompt

Database SQL Prompt

You can check the available database list using \l, i.e., backslash el command as follows −

postgres-# \l

List of databases

-----------+----------+----------+---------+-------+-----------------------

postgres | postgres | UTF8 | C | C |

template0 | postgres | UTF8 | C | C | =c/postgres +

template1 | postgres | UTF8 | C | C | =c/postgres +

testdb | postgres | UTF8 | C | C |

(4 rows)

postgres-#

Now, type the following command to connect/select a desired database; here, we will

connect to the testdb database.

postgres=# \c testdb;

psql (9.2.4)

Type "help" for help.

You are now connected to database "testdb" as user "postgres".

testdb=#

You can select your database from the command prompt itself at the time when you login

to your database. Following is a simple example −

psql -h localhost -p 5432 -U postgress testdb

Password for user postgress: ****

psql (9.2.4)

Type "help" for help.

You are now connected to database "testdb" as user "postgres".

testdb=#

You are now logged into PostgreSQL testdb and ready to execute your commands inside

testdb. To exit from the database, you can use the command \q.

PostgreSQL - DROP DatabasePostgreSQL - DROP Database

PostgreSQL - DROP Database

In this chapter, we will discuss how to delete the database in PostgreSQL. There are two

options to delete a database −

Using DROP DATABASE, an SQL command.

Using dropdb a command-line executable.

Be careful before using this operation because deleting an existing database would

result in loss of complete information stored in the database.

OS Command PromptOS Command Prompt

OS Command Prompt

This command drops a database. It removes the catalog entries for the database and

deletes the directory containing the data. It can only be executed by the database owner.

This command cannot be executed while you or anyone else is connected to the target

database (connect to postgres or any other database to issue this command).

The syntax for DROP DATABASE is given below −

DROP DATABASE [ IF EXISTS ] name

The table lists the parameters with their descriptions.

S. No. Parameter & Description

IF EXISTS

Do not throw an error if the database does not exist. A notice is issued in this

case.

name

The name of the database to remove.

We cannot drop a database that has any open connections, including our own

connection from psql or pgAdmin III. We must switch to another database or

template1 if we want to delete the database we are currently connected to. Thus, it

might be more convenient to use the program dropdb instead, which is a wrapper

around this command.

The following is a simple example, which will delete testdb from your PostgreSQL schema

−

postgres=# DROP DATABASE testdb;

postgres-#

PostgresSQL command line executable dropdb is a command-line wrapper around the SQL

command DROP DATABASE. There is no effective difference between dropping databases

via this utility and via other methods for accessing the server. dropdb destroys an existing

Using DROP DATABASEUsing DROP DATABASE

Using DROP DATABASE

SyntaxSyntax

Syntax

ParametersParameters

Parameters

ExampleExample

Example

Using dropdb CommandUsing dropdb Command

Using dropdb Command

PostgreSQL database. The user, who executes this command must be a database super

user or the owner of the database.

The syntax for dropdb is as shown below −

dropdb [option...] dbname

The following table lists the parameters with their descriptions

S. No. Parameter & Description

dbname

The name of a database to be deleted.

option

command-line arguments, which dropdb accepts.

The following table lists the command-line arguments dropdb accepts −

S. No. Option & Description

-e

Shows the commands being sent to the server.

-i

Issues a verification prompt before doing anything destructive.

-V

Print the dropdb version and exit.

--if-exists

Do not throw an error if the database does not exist. A notice is issued in this

case.

5--help

Show help about dropdb command-line arguments, and exit.

SyntaxSyntax

Syntax

ParametersParameters

Parameters

OptionsOptions

Options

-h host

Specifies the host name of the machine on which the server is running.

-p port

Specifies the TCP port or the local UNIX domain socket file extension on which

the server is listening for connections.

-U username

User name to connect as.

-w

Never issue a password prompt.

-W

Force dropdb to prompt for a password before connecting to a database.

--maintenance-db=dbname

Specifies the name of the database to connect to in order to drop the target

database.

The following example demonstrates deleting a database from OS command prompt −

dropdb -h localhost -p 5432 -U postgress testdb

Password for user postgress: ****

The above command drops the database testdb. Here, I have used the postgres (found

under the pg_roles of template1) username to drop the database.

PostgreSQL - CREATE TablePostgreSQL - CREATE Table

PostgreSQL - CREATE Table

The PostgreSQL CREATE TABLE statement is used to create a new table in any of the given

database.

Basic syntax of CREATE TABLE statement is as follows −

ExampleExample

Example

SyntaxSyntax

Syntax

CREATE TABLE table_name(

column1 datatype,

column2 datatype,

column3 datatype,

.....

columnN datatype,

PRIMARY KEY( one or more columns )

);

CREATE TABLE is a keyword, telling the database system to create a new table. The unique

name or identifier for the table follows the CREATE TABLE statement. Initially, the empty

table in the current database is owned by the user issuing the command.

Then, in brackets, comes the list, defining each column in the table and what sort of data

type it is. The syntax will become clear with an example given below.

The following is an example, which creates a COMPANY table with ID as primary key and

NOT NULL are the constraints showing that these fields cannot be NULL while creating

records in this table −

CREATE TABLE COMPANY(

ID INT PRIMARY KEY NOT NULL,

NAME TEXT NOT NULL,

AGE INT NOT NULL,

ADDRESS CHAR(50),

SALARY REAL

);

Let us create one more table, which we will use in our exercises in subsequent chapters −

CREATE TABLE DEPARTMENT(

ID INT PRIMARY KEY NOT NULL,

DEPT CHAR(50) NOT NULL,

EMP_ID INT NOT NULL

);

You can verify if your table has been created successfully using \d command, which will be

used to list down all the tables in an attached database.

testdb-# \d

The above given PostgreSQL statement will produce the following result −

List of relations

Schema | Name | Type | Owner

--------+------------+-------+----------

public | company | table | postgres

ExamplesExamples

Examples

public | department | table | postgres

(2 rows)

Use \d tablename to describe each table as shown below −

testdb-# \d company

The above given PostgreSQL statement will produce the following result −

Table "public.company"

Column | Type | Modifiers

-----------+---------------+-----------

id | integer | not null

name | text | not null

age | integer | not null

address | character(50) |

salary | real |

join_date | date |

Indexes:

"company_pkey" PRIMARY KEY, btree (id)

PostgreSQL - DROP TablePostgreSQL - DROP Table

PostgreSQL - DROP Table

The PostgreSQL DROP TABLE statement is used to remove a table definition and all

associated data, indexes, rules, triggers, and constraints for that table.

You have to be careful while using this command because once a table is deleted

then all the information available in the table would also be lost forever.

Basic syntax of DROP TABLE statement is as follows −

DROP TABLE table_name;

We had created the tables DEPARTMENT and COMPANY in the previous chapter. First,

verify these tables (use \d to list the tables) −

testdb-# \d

This would produce the following result −

List of relations

Schema | Name | Type | Owner

SyntaxSyntax

Syntax

ExampleExample

Example

--------+------------+-------+----------

public | company | table | postgres

public | department | table | postgres

(2 rows)

This means DEPARTMENT and COMPANY tables are present. So let us drop them as follows

−

testdb=# drop table department, company;

This would produce the following result −

DROP TABLE

testdb=# \d

relations found.

testdb=#

The message returned DROP TABLE indicates that drop command is executed successfully.

PostgreSQL - SchemaPostgreSQL - Schema

PostgreSQL - Schema

A schema is a named collection of tables. A schema can also contain views, indexes,

sequences, data types, operators, and functions. Schemas are analogous to directories at

the operating system level, except that schemas cannot be nested. PostgreSQL statement

CREATE SCHEMA creates a schema.

The basic syntax of CREATE SCHEMA is as follows −

CREATE SCHEMA name;

Where name is the name of the schema.

The basic syntax to create table in schema is as follows −

CREATE TABLE myschema.mytable (

...

);

Let us see an example for creating a schema. Connect to the database testdb and create a

schema myschema as follows −

testdb=# create schema myschema;

CREATE SCHEMA

SyntaxSyntax

Syntax

Syntax to Create Table in SchemaSyntax to Create Table in Schema

Syntax to Create Table in Schema

ExampleExample

Example

The message "CREATE SCHEMA" signifies that the schema is created successfully.

Now, let us create a table in the above schema as follows −

testdb=# create table myschema.company(

ID INT NOT NULL,

NAME VARCHAR (20) NOT NULL,

AGE INT NOT NULL,

ADDRESS CHAR (25),

SALARY DECIMAL (18, 2),

PRIMARY KEY (ID)

);

This will create an empty table. You can verify the table created with the command given

below −

testdb=# select * from myschema.company;

This would produce the following result −

id | name | age | address | salary

----+------+-----+---------+--------

(0 rows)

To drop a schema if it is empty (all objects in it have been dropped), use the command −

DROP SCHEMA myschema;

To drop a schema including all contained objects, use the command −

DROP SCHEMA myschema CASCADE;

It allows many users to use one database without interfering with each other.

It organizes database objects into logical groups to make them more manageable.

Third-party applications can be put into separate schemas so they do not collide

with the names of other objects.

PostgreSQL - INSERT QueryPostgreSQL - INSERT Query

PostgreSQL - INSERT Query

The PostgreSQL INSERT INTO statement allows one to insert new rows into a table. One

can insert a single row at a time or several rows as a result of a query.

Syntax to Drop SchemaSyntax to Drop Schema

Syntax to Drop Schema

Advantages of using a SchemaAdvantages of using a Schema

Advantages of using a Schema

SyntaxSyntax

Syntax

Basic syntax of INSERT INTO statement is as follows −

INSERT INTO TABLE_NAME (column1, column2, column3,...columnN)

VALUES (value1, value2, value3,...valueN);

Here, column1, column2,...columnN are the names of the columns in the table into

which you want to insert data.

The target column names can be listed in any order. The values supplied by the

VALUES clause or query are associated with the explicit or implicit column list left-

to-right.

You may not need to specify the column(s) name in the SQL query if you are adding values

for all the columns of the table. However, make sure the order of the values is in the same

order as the columns in the table. The SQL INSERT INTO syntax would be as follows −

INSERT INTO TABLE_NAME VALUES (value1,value2,value3,...valueN);

The following table summarizes the output messages and their meaning −

S. No. Output Message & Description

INSERT oid 1

Message returned if only one row was inserted. oid is the numeric OID of the

inserted row.

INSERT 0 #

Message returned if more than one rows were inserted. # is the number of

rows inserted.

Let us create COMPANY table in testdb as follows −

CREATE TABLE COMPANY(

ID INT PRIMARY KEY NOT NULL,

NAME TEXT NOT NULL,

AGE INT NOT NULL,

ADDRESS CHAR(50),

SALARY REAL,

JOIN_DATE DATE

);

OutputOutput

Output

ExamplesExamples

Examples

The following example inserts a row into the COMPANY table −

The following example is to insert a row; here salary column is omitted and therefore it will

have the default value −

The following example uses the DEFAULT clause for the JOIN_DATE column rather than

specifying a value −

The following example inserts multiple rows using the multirow VALUES syntax −

All the above statements would create the following records in COMPANY table. The next

chapter will teach you how to display all these records from a table.

ID NAME AGE ADDRESS SALARY JOIN_DATE

---- ---------- ----- ---------- ------- --------

1 Paul 32 California 20000.0 2001-07-13

2 Allen 25 Texas 2007-12-13

3 Teddy 23 Norway 20000.0

4 Mark 25 Rich-Mond 65000.0 2007-12-13

5 David 27 Texas 85000.0 2007-12-13

PostgreSQL - SELECT QueryPostgreSQL - SELECT Query

PostgreSQL - SELECT Query

PostgreSQL SELECT statement is used to fetch the data from a database table, which

returns data in the form of result table. These result tables are called result-sets.

The basic syntax of SELECT statement is as follows −

SELECT column1, column2, columnN FROM table_name;

INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY,JOIN_DATE) VALUES (1, 'Paul', 32, 'California', 2

INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,JOIN_DATE) VALUES (2, 'Allen', 25, 'Texas', '2007-12-13'

INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY,JOIN_DATE) VALUES (3, 'Teddy', 23, 'Norway', 2000

INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY,JOIN_DATE) VALUES (4, 'Mark', 25, 'Rich-Mond ', 6

SyntaxSyntax

Syntax

Here, column1, column2...are the fields of a table, whose values you want to fetch. If you

want to fetch all the fields available in the field then you can use the following syntax −

SELECT * FROM table_name;

Consider the table COMPANY having records as follows −

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

The following is an example, which would fetch ID, Name and Salary fields of the

customers available in CUSTOMERS table −

testdb=# SELECT ID, NAME, SALARY FROM COMPANY ;

This would produce the following result −

id | name | salary

----+-------+--------

1 | Paul | 20000

2 | Allen | 15000

3 | Teddy | 20000

4 | Mark | 65000

5 | David | 85000

6 | Kim | 45000

7 | James | 10000

(7 rows)

If you want to fetch all the fields of CUSTOMERS table, then use the following query −

testdb=# SELECT * FROM COMPANY;

This would produce the following result −

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

ExampleExample

Example

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

PostgreSQL - OperatorsPostgreSQL - Operators

PostgreSQL - Operators

An operator is a reserved word or a character used primarily in a PostgreSQL statement's

WHERE clause to perform operation(s), such as comparisons and arithmetic operations.

Operators are used to specify conditions in a PostgreSQL statement and to serve as

conjunctions for multiple conditions in a statement.

Arithmetic operators

Comparison operators

Logical operators

Bitwise operators

Assume variable a holds 2 and variable b holds 3, then −

Example

Operator Description Example

+Addition - Adds values on either side of

the operator a + b will give 5

-Subtraction - Subtracts right hand

operand from left hand operand a - b will give -1

*Multiplication - Multiplies values on either

side of the operator a * b will give 6

/Division - Divides left hand operand by

right hand operand b / a will give 1

Modulus - Divides left hand operand by

right hand operand and returns

remainder

b % a will give 1

^Exponentiation - This gives the exponent

value of the right hand operand a ^ b will give 8

What is an Operator in PostgreSQL?What is an Operator in PostgreSQL?

What is an Operator in PostgreSQL?

PostgreSQL Arithmetic OperatorsPostgreSQL Arithmetic Operators

PostgreSQL Arithmetic Operators

|/ square root |/ 25.0 will give 5

||/ Cube root ||/ 27.0 will give 3

! factorial 5 ! will give 120

!! factorial (prefix operator) !! 5 will give 120

Assume variable a holds 10 and variable b holds 20, then −

Show Examples

Operator Description Example

=Checks if the values of two operands are equal or

not, if yes then condition becomes true. (a = b) is not true.

Checks if the values of two operands are equal or

not, if values are not equal then condition becomes

true.

(a != b) is true.

Checks if the values of two operands are equal or

not, if values are not equal then condition becomes

true.

(a <> b) is true.

Checks if the value of left operand is greater than

the value of right operand, if yes then condition

becomes true.

(a > b) is not true.

Checks if the value of left operand is less than the

value of right operand, if yes then condition

becomes true.

(a < b) is true.

Checks if the value of left operand is greater than

or equal to the value of right operand, if yes then

condition becomes true.

(a >= b) is not true.

Checks if the value of left operand is less than or

equal to the value of right operand, if yes then

condition becomes true.

(a <= b) is true.

Here is a list of all the logical operators available in PostgresSQL.

Show Examples

PostgreSQL Comparison OperatorsPostgreSQL Comparison Operators

PostgreSQL Comparison Operators

PostgreSQL Logical OperatorsPostgreSQL Logical Operators

PostgreSQL Logical Operators

S. No. Operator & Description

AND

The AND operator allows the existence of multiple conditions in a PostgresSQL

statement's WHERE clause.

NOT

The NOT operator reverses the meaning of the logical operator with which it is

used. Eg. NOT EXISTS, NOT BETWEEN, NOT IN etc. This is negate operator.

The OR operator is used to combine multiple conditions in a PostgresSQL

statement's WHERE clause.

Bitwise operator works on bits and performs bit-by-bit operation. The truth table for & and

| is as follows −

p q p & q p | q

0 0 0 0

0 1 0 1

1 1 1 1

1 0 0 1

Assume if A = 60; and B = 13; now in binary format they will be as follows −

A = 0011 1100

B = 0000 1101

-----------------

A&B = 0000 1100

A|B = 0011 1101

~A = 1100 0011

Show Examples

The Bitwise operators supported by PostgreSQL are listed in the following table −

PostgreSQL Bit String OperatorsPostgreSQL Bit String Operators

PostgreSQL Bit String Operators

Operator Description Example

&Binary AND Operator copies a bit to the

result if it exists in both operands. (A & B) will give 12 which is 0000 1100

|Binary OR Operator copies a bit if it

exists in either operand. (A | B) will give 61 which is 0011 1101

~Binary Ones Complement Operator is

unary and has the effect of 'flipping' bits.

(~A ) will give -61 which is 1100 0011

in 2's complement form due to a

signed binary number.

Binary Left Shift Operator. The left

operands value is moved left by the

number of bits specified by the right

operand.

A << 2 will give 240 which is 1111

0000

Binary Right Shift Operator. The left

operands value is moved right by the

number of bits specified by the right

operand.

A >> 2 will give 15 which is 0000 1111

# bitwise XOR. A # B will give 49 which is 0100 1001

PostgreSQL - ExpressionsPostgreSQL - Expressions

PostgreSQL - Expressions

An expression is a combination of one or more values, operators, and PostgresSQL

functions that evaluate to a value.

PostgreSQL EXPRESSIONS are like formulas and they are written in query language. You

can also use to query the database for specific set of data.

Consider the basic syntax of the SELECT statement as follows −

SELECT column1, column2, columnN

FROM table_name

WHERE [CONDITION | EXPRESSION];

There are different types of PostgreSQL expressions, which are mentioned below −

PostgreSQL Boolean Expressions fetch the data on the basis of matching single value.

Following is the syntax −

SELECT column1, column2, columnN

FROM table_name

SyntaxSyntax

Syntax

PostgreSQL - Boolean ExpressionsPostgreSQL - Boolean Expressions

PostgreSQL - Boolean Expressions

WHERE SINGLE VALUE MATCHTING EXPRESSION;

Consider the table COMPANY having records as follows −

testdb# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

Here is the simple example showing usage of PostgreSQL Boolean Expressions −

testdb=# SELECT * FROM COMPANY WHERE SALARY = 10000;

The above given PostgreSQL statement will produce the following result −

id | name | age | address | salary

----+-------+-----+----------+--------

7 | James | 24 | Houston | 10000

(1 row)

These expressions are used to perform any mathematical operation in any query. Following

is the syntax −

SELECT numerical_expression as OPERATION_NAME

[FROM table_name WHERE CONDITION] ;

Here numerical_expression is used for mathematical expression or any formula. Following

is a simple example showing usage of SQL Numeric Expressions −

testdb=# SELECT (15 + 6) AS ADDITION ;

The above given PostgreSQL statement will produce the following result −

addition

----------

(1 row)

There are several built-in functions like avg(), sum(), count() to perform what is known as

aggregate data calculations against a table or a specific table column.

testdb=# SELECT COUNT(*) AS "RECORDS" FROM COMPANY;

PostgreSQL - Numeric ExpressionPostgreSQL - Numeric Expression

PostgreSQL - Numeric Expression

The above given PostgreSQL statement will produce the following result −

RECORDS

---------

(1 row)

Date Expressions return the current system date and time values and these expressions

are used in various data manipulations.

testdb=# SELECT CURRENT_TIMESTAMP;

The above given PostgreSQL statement will produce the following result −

now

-------------------------------

2013-05-06 14:38:28.078+05:30

(1 row)

PostgreSQL - WHERE ClausePostgreSQL - WHERE Clause

PostgreSQL - WHERE Clause

The PostgreSQL WHERE clause is used to specify a condition while fetching the data from

single table or joining with multiple tables.

If the given condition is satisfied, only then it returns specific value from the table. You can

filter out rows that you do not want included in the result-set by using the WHERE clause.

The WHERE clause not only is used in SELECT statement, but it is also used in UPDATE,

DELETE statement, etc., which we would examine in subsequent chapters.

The basic syntax of SELECT statement with WHERE clause is as follows −

SELECT column1, column2, columnN

FROM table_name

WHERE [search_condition]

You can specify a search_condition using comparison or logical operators. like >, <, =,

LIKE, NOT, etc. The following examples would make this concept clear.

Consider the table COMPANY having records as follows −

PostgreSQL - Date ExpressionsPostgreSQL - Date Expressions

PostgreSQL - Date Expressions

SyntaxSyntax

Syntax

ExampleExample

Example

testdb# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

Here are simple examples showing usage of PostgreSQL Logical Operators. Following

SELECT statement will list down all the records where AGE is greater than or equal to 25

AND salary is greater than or equal to 65000.00 −

testdb=# SELECT * FROM COMPANY WHERE AGE >= 25 AND SALARY >= 65000;

The above given PostgreSQL statement will produce the following result −

id | name | age | address | salary

----+-------+-----+------------+--------

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

(2 rows)

The following SELECT statement lists down all the records where AGE is greater than or

equal to 25 OR salary is greater than or equal to 65000.00 −

testdb=# SELECT * FROM COMPANY WHERE AGE >= 25 OR SALARY >= 65000;

The above given PostgreSQL statement will produce the following result −

id | name | age | address | salary

----+-------+-----+-------------+--------

1 | Paul | 32 | California | 20000

2 | Allen | 25 | Texas | 15000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

(4 rows)

The following SELECT statement lists down all the records where AGE is not NULL which

means all the records, because none of the record has AGE equal to NULL −

testdb=# SELECT * FROM COMPANY WHERE AGE IS NOT NULL;

The above given PostgreSQL statement will produce the following result −

id | name | age | address | salary

----+-------+-----+------------+--------

1 | Paul | 32 | California | 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

(7 rows)

The following SELECT statement lists down all the records where NAME starts with 'Pa',

does not matter what comes after 'Pa'.

testdb=# SELECT * FROM COMPANY WHERE NAME LIKE 'Pa%';

The above given PostgreSQL statement will produce the following result −

id | name | age |address | salary

----+------+-----+-----------+--------

1 | Paul | 32 | California| 20000

The following SELECT statement lists down all the records where AGE value is either 25 or

27 −

testdb=# SELECT * FROM COMPANY WHERE AGE IN ( 25, 27 );

The above given PostgreSQL statement will produce the following result −

id | name | age | address | salary

----+-------+-----+------------+--------

2 | Allen | 25 | Texas | 15000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

(3 rows)

The following SELECT statement lists down all the records where AGE value is neither 25

nor 27 −

testdb=# SELECT * FROM COMPANY WHERE AGE NOT IN ( 25, 27 );

The above given PostgreSQL statement will produce the following result −

id | name | age | address | salary

----+-------+-----+------------+--------

1 | Paul | 32 | California | 20000

3 | Teddy | 23 | Norway | 20000

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

(4 rows)

The following SELECT statement lists down all the records where AGE value is in BETWEEN

25 AND 27 −

testdb=# SELECT * FROM COMPANY WHERE AGE BETWEEN 25 AND 27;

The above given PostgreSQL statement will produce the following result −

id | name | age | address | salary

----+-------+-----+------------+--------

2 | Allen | 25 | Texas | 15000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

(3 rows)

The following SELECT statement makes use of SQL subquery where subquery finds all the

records with AGE field having SALARY > 65000 and later WHERE clause is being used

along with EXISTS operator to list down all the records where AGE from the outside query

exists in the result returned by sub-query −

testdb=# SELECT AGE FROM COMPANY

WHERE EXISTS (SELECT AGE FROM COMPANY WHERE SALARY > 65000);

The above given PostgreSQL statement will produce the following result −

age

-----

(7 rows)

The following SELECT statement makes use of SQL subquery where subquery finds all the

records with AGE field having SALARY > 65000 and later WHERE clause is being used

along with > operator to list down all the records where AGE from outside query is greater

than the age in the result returned by sub-query −

testdb=# SELECT * FROM COMPANY

WHERE AGE > (SELECT AGE FROM COMPANY WHERE SALARY > 65000);

The above given PostgreSQL statement will produce the following result −

id | name | age | address | salary

----+------+-----+------------+--------

1 | Paul | 32 | California | 20000

AND and OR Conjunctive OperatorsAND and OR Conjunctive Operators

AND and OR Conjunctive Operators

The PostgreSQL AND and OR operators are used to combine multiple conditions to narrow

down selected data in a PostgreSQL statement. These two operators are called conjunctive

operators.

These operators provide a means to make multiple comparisons with different operators in

the same PostgreSQL statement.

The AND operator allows the existence of multiple conditions in a PostgreSQL statement's

WHERE clause. While using AND operator, complete condition will be assumed true when

all the conditions are true. For example [condition1] AND [condition2] will be true only

when both condition1 and condition2 are true.

The basic syntax of AND operator with WHERE clause is as follows −

SELECT column1, column2, columnN

FROM table_name

WHERE [condition1] AND [condition2]...AND [conditionN];

You can combine N number of conditions using AND operator. For an action to be taken by

the PostgreSQL statement, whether it be a transaction or query, all conditions separated

by the AND must be TRUE.

Consider the table COMPANY having records as follows −

testdb# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

The following SELECT statement lists down all the records where AGE is greater than or

equal to 25 AND salary is greater than or equal to 65000.00 −

The AND OperatorThe AND Operator

The AND Operator

SyntaxSyntax

Syntax

ExampleExample

Example

testdb=# SELECT * FROM COMPANY WHERE AGE >= 25 AND SALARY >= 65000;

The above given PostgreSQL statement will produce the following result −

id | name | age | address | salary

----+-------+-----+------------+--------

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

(2 rows)

The OR operator is also used to combine multiple conditions in a PostgreSQL statement's

WHERE clause. While using OR operator, complete condition will be assumed true when at

least any of the conditions is true. For example [condition1] OR [condition2] will be true if

either condition1 or condition2 is true.

The basic syntax of OR operator with WHERE clause is as follows −

SELECT column1, column2, columnN

FROM table_name

WHERE [condition1] OR [condition2]...OR [conditionN]

You can combine N number of conditions using OR operator. For an action to be taken by

the PostgreSQL statement, whether it be a transaction or query, only any ONE of the

conditions separated by the OR must be TRUE.

Consider the COMPANY table, having the following records −

# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

The following SELECT statement lists down all the records where AGE is greater than or

equal to 25 OR salary is greater than or equal to 65000.00 −

testdb=# SELECT * FROM COMPANY WHERE AGE >= 25 OR SALARY >= 65000;

The above given PostgreSQL statement will produce the following result −

The OR OperatorThe OR Operator

The OR Operator

SyntaxSyntax

Syntax

ExampleExample

Example

id | name | age | address | salary

----+-------+-----+------------+--------

1 | Paul | 32 | California | 20000

2 | Allen | 25 | Texas | 15000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

(4 rows)

PostgreSQL - UPDATE QueryPostgreSQL - UPDATE Query

PostgreSQL - UPDATE Query

The PostgreSQL UPDATE Query is used to modify the existing records in a table. You can

use WHERE clause with UPDATE query to update the selected rows. Otherwise, all the rows

would be updated.

The basic syntax of UPDATE query with WHERE clause is as follows −

UPDATE table_name

SET column1 = value1, column2 = value2...., columnN = valueN

WHERE [condition];

You can combine N number of conditions using AND or OR operators.

Consider the table COMPANY , having records as follows −

testdb# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

The following is an example, which would update ADDRESS for a customer, whose ID is 6

−

testdb=# UPDATE COMPANY SET SALARY = 15000 WHERE ID = 3;

Now, COMPANY table would have the following records −

id | name | age | address | salary

----+-------+-----+------------+--------

1 | Paul | 32 | California | 20000

SyntaxSyntax

Syntax

ExampleExample

Example

2 | Allen | 25 | Texas | 15000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

3 | Teddy | 23 | Norway | 15000

(7 rows)

If you want to modify all ADDRESS and SALARY column values in COMPANY table, you do

not need to use WHERE clause and UPDATE query would be as follows −

testdb=# UPDATE COMPANY SET ADDRESS = 'Texas', SALARY=20000;

Now, COMPANY table will have the following records −

id | name | age | address | salary

----+-------+-----+---------+--------

1 | Paul | 32 | Texas | 20000

2 | Allen | 25 | Texas | 20000

4 | Mark | 25 | Texas | 20000

5 | David | 27 | Texas | 20000

6 | Kim | 22 | Texas | 20000

7 | James | 24 | Texas | 20000

3 | Teddy | 23 | Texas | 20000

(7 rows)

PostgreSQL - DELETE QueryPostgreSQL - DELETE Query

PostgreSQL - DELETE Query

The PostgreSQL DELETE Query is used to delete the existing records from a table. You can

use WHERE clause with DELETE query to delete the selected rows. Otherwise, all the

records would be deleted.

The basic syntax of DELETE query with WHERE clause is as follows −

DELETE FROM table_name

WHERE [condition];

You can combine N number of conditions using AND or OR operators.

Consider the table COMPANY , having records as follows −

# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

SyntaxSyntax

Syntax

ExampleExample

Example

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

The following is an example, which would DELETE a customer whose ID is 7 −

testdb=# DELETE FROM COMPANY WHERE ID = 2;

Now, COMPANY table will have the following records −

id | name | age | address | salary

----+-------+-----+-------------+--------

1 | Paul | 32 | California | 20000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

(6 rows)

If you want to DELETE all the records from COMPANY table, you do not need to use WHERE

clause with DELETE queries, which would be as follows −

testdb=# DELETE FROM COMPANY;

Now, COMPANY table does not have any record because all the records have been deleted

by the DELETE statement.

PostgreSQL - LIKE ClausePostgreSQL - LIKE Clause

PostgreSQL - LIKE Clause

The PostgreSQL LIKE operator is used to match text values against a pattern using

wildcards. If the search expression can be matched to the pattern expression, the LIKE

operator will return true, which is 1.

There are two wildcards used in conjunction with the LIKE operator −

The percent sign (%)

The underscore (_)

The percent sign represents zero, one, or multiple numbers or characters. The underscore

represents a single number or character. These symbols can be used in combinations.

If either of these two signs is not used in conjunction with the LIKE clause, then the LIKE

acts like the equals operator.

The basic syntax of % and _ is as follows −

SyntaxSyntax

Syntax

SELECT FROM table_name

WHERE column LIKE 'XXXX%'

SELECT FROM table_name

WHERE column LIKE '%XXXX%'

SELECT FROM table_name

WHERE column LIKE 'XXXX_'

SELECT FROM table_name

WHERE column LIKE '_XXXX'

SELECT FROM table_name

WHERE column LIKE '_XXXX_'

You can combine N number of conditions using AND or OR operators. Here XXXX could be

any numeric or string value.

Here are number of examples showing WHERE part having different LIKE clause with '%'

and '_' operators −

S. No. Statement & Description

WHERE SALARY::text LIKE '200%'

Finds any values that start with 200

WHERE SALARY::text LIKE '%200%'

Finds any values that have 200 in any position

WHERE SALARY::text LIKE '_00%'

Finds any values that have 00 in the second and third positions

ExampleExample

Example

WHERE SALARY::text LIKE '2_%_%'

Finds any values that start with 2 and are at least 3 characters in length

WHERE SALARY::text LIKE '%2'

Finds any values that end with 2

WHERE SALARY::text LIKE '_2%3'

Finds any values that have 2 in the second position and end with a 3

WHERE SALARY::text LIKE '2___3'

Finds any values in a five-digit number that start with 2 and end with 3

Postgres LIKE is String compare only. Hence, we need to explicitly cast the integer

column to string as in the examples above.

Let us take a real example, consider the table COMPANY , having records as follows −

# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

The following is an example, which would display all the records from COMPANY table

where AGE starts with 2 −

testdb=# SELECT * FROM COMPANY WHERE AGE::text LIKE '2%';

This would produce the following result −

id | name | age | address | salary

----+-------+-----+-------------+--------

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

8 | Paul | 24 | Houston | 20000

(7 rows)

The following is an example, which would display all the records from COMPANY table

where ADDRESS will have a hyphen (-) inside the text −

testdb=# SELECT * FROM COMPANY WHERE ADDRESS LIKE '%-%';

This would produce the following result −

id | name | age | address | salary

----+------+-----+-------------------------------------------+--------

4 | Mark | 25 | Rich-Mond | 65000

6 | Kim | 22 | South-Hall | 45000

(2 rows)

PostgreSQL - LIMIT ClausePostgreSQL - LIMIT Clause

PostgreSQL - LIMIT Clause

The PostgreSQL LIMIT clause is used to limit the data amount returned by the SELECT

statement.

The basic syntax of SELECT statement with LIMIT clause is as follows −

SELECT column1, column2, columnN

FROM table_name

LIMIT [no of rows]

The following is the syntax of LIMIT clause when it is used along with OFFSET clause −

SELECT column1, column2, columnN

FROM table_name

LIMIT [no of rows] OFFSET [row num]

LIMIT and OFFSET allow you to retrieve just a portion of the rows that are generated by

the rest of the query.

Consider the table COMPANY having records as follows −

# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

SyntaxSyntax

Syntax

ExampleExample

Example

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

The following is an example, which limits the row in the table according to the number of

rows you want to fetch from table −

testdb=# SELECT * FROM COMPANY LIMIT 4;

This would produce the following result −

id | name | age | address | salary

----+-------+-----+-------------+--------

1 | Paul | 32 | California | 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

(4 rows)

However, in certain situation, you may need to pick up a set of records from a particular

offset. Here is an example, which picks up three records starting from the third position −

testdb=# SELECT * FROM COMPANY LIMIT 3 OFFSET 2;

This would produce the following result −

id | name | age | address | salary

----+-------+-----+-----------+--------

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

(3 rows)

PostgreSQL - ORDER BY ClausePostgreSQL - ORDER BY Clause

PostgreSQL - ORDER BY Clause

The PostgreSQL ORDER BY clause is used to sort the data in ascending or descending

order, based on one or more columns.

The basic syntax of ORDER BY clause is as follows −

SELECT column-list

FROM table_name

[WHERE condition]

[ORDER BY column1, column2, .. columnN] [ASC | DESC];

SyntaxSyntax

Syntax

You can use more than one column in the ORDER BY clause. Make sure whatever column

you are using to sort, that column should be available in column-list.

Consider the table COMPANY having records as follows −

testdb# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

The following is an example, which would sort the result in ascending order by SALARY −

testdb=# SELECT * FROM COMPANY ORDER BY AGE ASC;

This would produce the following result −

id | name | age | address | salary

----+-------+-----+------------+--------

6 | Kim | 22 | South-Hall | 45000

3 | Teddy | 23 | Norway | 20000

7 | James | 24 | Houston | 10000

8 | Paul | 24 | Houston | 20000

4 | Mark | 25 | Rich-Mond | 65000

2 | Allen | 25 | Texas | 15000

5 | David | 27 | Texas | 85000

1 | Paul | 32 | California | 20000

9 | James | 44 | Norway | 5000

10 | James | 45 | Texas | 5000

(10 rows)

The following is an example, which would sort the result in ascending order by NAME and

SALARY −

testdb=# SELECT * FROM COMPANY ORDER BY NAME, SALARY ASC;

This would produce the following result −

id | name | age | address | salary

----+-------+-----+--------------+--------

2 | Allen | 25 | Texas | 15000

ExampleExample

Example

5 | David | 27 | Texas | 85000

10 | James | 45 | Texas | 5000

9 | James | 44 | Norway | 5000

7 | James | 24 | Houston | 10000

6 | Kim | 22 | South-Hall | 45000

4 | Mark | 25 | Rich-Mond | 65000

1 | Paul | 32 | California | 20000

8 | Paul | 24 | Houston | 20000

3 | Teddy | 23 | Norway | 20000

(10 rows)

The following is an example, which would sort the result in descending order by NAME −

testdb=# SELECT * FROM COMPANY ORDER BY NAME DESC;

This would produce the following result −

id | name | age | address | salary

----+-------+-----+------------+--------

3 | Teddy | 23 | Norway | 20000

1 | Paul | 32 | California | 20000

8 | Paul | 24 | Houston | 20000

4 | Mark | 25 | Rich-Mond | 65000

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

9 | James | 44 | Norway | 5000

10 | James | 45 | Texas | 5000

5 | David | 27 | Texas | 85000

2 | Allen | 25 | Texas | 15000

(10 rows)

PostgreSQL - GROUP BYPostgreSQL - GROUP BY

PostgreSQL - GROUP BY

The PostgreSQL GROUP BY clause is used in collaboration with the SELECT statement to

group together those rows in a table that have identical data. This is done to eliminate

redundancy in the output and/or compute aggregates that apply to these groups.

The GROUP BY clause follows the WHERE clause in a SELECT statement and precedes the

ORDER BY clause.

The basic syntax of GROUP BY clause is given below. The GROUP BY clause must follow the

conditions in the WHERE clause and must precede the ORDER BY clause if one is used.

SyntaxSyntax

Syntax

SELECT column-list

FROM table_name

WHERE [ conditions ]

GROUP BY column1, column2....columnN

ORDER BY column1, column2....columnN

You can use more than one column in the GROUP BY clause. Make sure whatever column

you are using to group, that column should be available in column-list.

Consider the table COMPANY having records as follows −

# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

If you want to know the total amount of salary of each customer, then GROUP BY query

would be as follows −

testdb=# SELECT NAME, SUM(SALARY) FROM COMPANY GROUP BY NAME;

This would produce the following result −

name | sum

-------+-------

Teddy | 20000

Paul | 20000

Mark | 65000

David | 85000

Allen | 15000

Kim | 45000

James | 10000

(7 rows)

Now, let us create three more records in COMPANY table using the following INSERT

statements −

INSERT INTO COMPANY VALUES (8, 'Paul', 24, 'Houston', 20000.00);

INSERT INTO COMPANY VALUES (9, 'James', 44, 'Norway', 5000.00);

INSERT INTO COMPANY VALUES (10, 'James', 45, 'Texas', 5000.00);

ExampleExample

Example

Now, our table has the following records with duplicate names −

id | name | age | address | salary

----+-------+-----+--------------+--------

1 | Paul | 32 | California | 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

8 | Paul | 24 | Houston | 20000

9 | James | 44 | Norway | 5000

10 | James | 45 | Texas | 5000

(10 rows)

Again, let us use the same statement to group-by all the records using NAME column as

follows −

testdb=# SELECT NAME, SUM(SALARY) FROM COMPANY GROUP BY NAME ORDER BY NAME;

This would produce the following result −

name | sum

-------+-------

Allen | 15000

David | 85000

James | 20000

Kim | 45000

Mark | 65000

Paul | 40000

Teddy | 20000

(7 rows)

Let us use ORDER BY clause along with GROUP BY clause as follows −

testdb=# SELECT NAME, SUM(SALARY)

FROM COMPANY GROUP BY NAME ORDER BY NAME DESC;

This would produce the following result −

name | sum

-------+-------

Teddy | 20000

Paul | 40000

Mark | 65000

Kim | 45000

James | 20000

David | 85000

Allen | 15000

(7 rows)

PostgreSQL - WITH ClausePostgreSQL - WITH Clause

PostgreSQL - WITH Clause

In PostgreSQL, the WITH query provides a way to write auxiliary statements for use in a

larger query. It helps in breaking down complicated and large queries into simpler forms,

which are easily readable. These statements often referred to as Common Table

Expressions or CTEs, can be thought of as defining temporary tables that exist just for one

query.

The WITH query being CTE query, is particularly useful when subquery is executed multiple

times. It is equally helpful in place of temporary tables. It computes the aggregation once

and allows us to reference it by its name (may be multiple times) in the queries.

The WITH clause must be defined before it is used in the query.

The basic syntax of WITH query is as follows −

WITH

name_for_summary_data AS (

SELECT Statement)

SELECT columns

FROM name_for_summary_data

WHERE conditions <=> (

SELECT column

FROM name_for_summary_data)

[ORDER BY columns]

Where name_for_summary_data is the name given to the WITH clause. The

name_for_summary_data can be the same as an existing table name and will take

precedence.

You can use data-modifying statements (INSERT, UPDATE or DELETE) in WITH. This allows

you to perform several different operations in the same query.

Recursive WITH or Hierarchical queries, is a form of CTE where a CTE can reference to itself, i.e., a

WITH query can refer to its own output, hence the name recursive.

Consider the table COMPANY having records as follows −

testdb# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

SyntaxSyntax

Syntax

Recursive WITHRecursive WITH

Recursive WITH

ExampleExample

Example

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

Now, let us write a query using the WITH clause to select the records from the above

table, as follows −

With CTE AS

(Select

, NAME

, AGE

, ADDRESS

, SALARY

FROM COMPANY )

Select * From CTE;

The above given PostgreSQL statement will produce the following result −

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

Now, let us write a query using the RECURSIVE keyword along with the WITH clause, to

find the sum of the salaries less than 20000, as follows −

WITH RECURSIVE t(n) AS (

VALUES (0)

UNION ALL

SELECT SALARY FROM COMPANY WHERE SALARY < 20000

)

SELECT sum(n) FROM t;

The above given PostgreSQL statement will produce the following result −

sum

-------

25000

(1 row)

Let us write a query using data modifying statements along with the WITH clause, as

shown below.

First, create a table COMPANY1 similar to the table COMPANY. The query in the example

effectively moves rows from COMPANY to COMPANY1. The DELETE in WITH deletes the

specified rows from COMPANY, returning their contents by means of its RETURNING clause;

and then the primary query reads that output and inserts it into COMPANY1 TABLE −

CREATE TABLE COMPANY1(

ID INT PRIMARY KEY NOT NULL,

NAME TEXT NOT NULL,

AGE INT NOT NULL,

ADDRESS CHAR(50),

SALARY REAL

);

WITH moved_rows AS (

DELETE FROM COMPANY

WHERE

SALARY >= 30000

RETURNING *

)

INSERT INTO COMPANY1 (SELECT * FROM moved_rows);

The above given PostgreSQL statement will produce the following result −

INSERT 0 3

Now, the records in the tables COMPANY and COMPANY1 are as follows −

testdb=# SELECT * FROM COMPANY;

id | name | age | address | salary

----+-------+-----+------------+--------

1 | Paul | 32 | California | 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

7 | James | 24 | Houston | 10000

(4 rows)

testdb=# SELECT * FROM COMPANY1;

id | name | age | address | salary

----+-------+-----+-------------+--------

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall | 45000

(3 rows)

PostgreSQL - HAVING ClausePostgreSQL - HAVING Clause

PostgreSQL - HAVING Clause

The HAVING clause allows us to pick out particular rows where the function's result meets

some condition.

The WHERE clause places conditions on the selected columns, whereas the HAVING clause

places conditions on groups created by the GROUP BY clause.

The following is the position of the HAVING clause in a SELECT query −

SELECT

FROM

WHERE

GROUP BY

HAVING

ORDER BY

The HAVING clause must follow the GROUP BY clause in a query and must also precede the

ORDER BY clause if used. The following is the syntax of the SELECT statement, including

the HAVING clause −

SELECT column1, column2

FROM table1, table2

WHERE [ conditions ]

GROUP BY column1, column2

HAVING [ conditions ]

ORDER BY column1, column2

Consider the table COMPANY having records as follows −

# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

The following is an example, which would display record for which the name count is less

than 2 −

testdb-# SELECT NAME FROM COMPANY GROUP BY name HAVING count(name) < 2;

This would produce the following result −

name

-------

Teddy

Paul

SyntaxSyntax

Syntax

ExampleExample

Example

Mark

David

Allen

Kim

James

(7 rows)

Now, let us create three more records in COMPANY table using the following INSERT

statements −

INSERT INTO COMPANY VALUES (8, 'Paul', 24, 'Houston', 20000.00);

INSERT INTO COMPANY VALUES (9, 'James', 44, 'Norway', 5000.00);

INSERT INTO COMPANY VALUES (10, 'James', 45, 'Texas', 5000.00);

Now, our table has the following records with duplicate names −

id | name | age | address | salary

----+-------+-----+--------------+--------

1 | Paul | 32 | California | 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

8 | Paul | 24 | Houston | 20000

9 | James | 44 | Norway | 5000

10 | James | 45 | Texas | 5000

(10 rows)

The following is the example, which would display record for which the name count is

greater than 1 −

testdb-# SELECT NAME FROM COMPANY GROUP BY name HAVING count(name) > 1;

This would produce the following result −

name

-------

Paul

James

(2 rows)

PostgreSQL - DISTINCT KeywordPostgreSQL - DISTINCT Keyword

PostgreSQL - DISTINCT Keyword

The PostgreSQL DISTINCT keyword is used in conjunction with SELECT statement to

eliminate all the duplicate records and fetching only unique records.

There may be a situation when you have multiple duplicate records in a table. While

fetching such records, it makes more sense to fetch only unique records instead of fetching

duplicate records.

The basic syntax of DISTINCT keyword to eliminate duplicate records is as follows −

SELECT DISTINCT column1, column2,.....columnN

FROM table_name

WHERE [condition]

Consider the table COMPANY having records as follows −

# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

Let us add two more records to this table as follows −

INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)

VALUES (8, 'Paul', 32, 'California', 20000.00 );

INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)

VALUES (9, 'Allen', 25, 'Texas', 15000.00 );

Now, the records in the COMPANY table would be −

id | name | age | address | salary

----+-------+-----+------------+--------

1 | Paul | 32 | California | 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

8 | Paul | 32 | California | 20000

9 | Allen | 25 | Texas | 15000

(9 rows)

First, let us see how the following SELECT query returns duplicate salary records −

testdb=# SELECT name FROM COMPANY;

This would produce the following result −

SyntaxSyntax

Syntax

ExampleExample

Example

name

-------

Paul

Allen

Teddy

Mark

David

Kim

James

Paul

Allen

(9 rows)

Now, let us use DISTINCT keyword with the above SELECT query and see the result −

testdb=# SELECT DISTINCT name FROM COMPANY;

This would produce the following result where we do not have any duplicate entry −

name

-------

Teddy

Paul

Mark

David

Allen

Kim

James

(7 rows)

PostgreSQL - CONSTRAINTSPostgreSQL - CONSTRAINTS

PostgreSQL - CONSTRAINTS

Constraints are the rules enforced on data columns on table. These are used to prevent

invalid data from being entered into the database. This ensures the accuracy and reliability

of the data in the database.

Constraints could be column level or table level. Column level constraints are applied only

to one column whereas table level constraints are applied to the whole table. Defining a

data type for a column is a constraint in itself. For example, a column of type DATE

constrains the column to valid dates.

The following are commonly used constraints available in PostgreSQL.

NOT NULL Constraint − Ensures that a column cannot have NULL value.

UNIQUE Constraint − Ensures that all values in a column are different.

PRIMARY Key − Uniquely identifies each row/record in a database table.

FOREIGN Key − Constrains data based on columns in other tables.

CHECK Constraint − The CHECK constraint ensures that all values in a column

satisfy certain conditions.

EXCLUSION Constraint − The EXCLUDE constraint ensures that if any two rows

are compared on the specified column(s) or expression(s) using the specified

operator(s), not all of these comparisons will return TRUE.

By default, a column can hold NULL values. If you do not want a column to have a NULL

value, then you need to define such constraint on this column specifying that NULL is now

not allowed for that column. A NOT NULL constraint is always written as a column

constraint.

A NULL is not the same as no data; rather, it represents unknown data.

For example, the following PostgreSQL statement creates a new table called COMPANY1

and adds five columns, three of which, ID and NAME and AGE, specify not to accept NULL

values −

CREATE TABLE COMPANY1(

ID INT PRIMARY KEY NOT NULL,

NAME TEXT NOT NULL,

AGE INT NOT NULL,

ADDRESS CHAR(50),

SALARY REAL

);

The UNIQUE Constraint prevents two records from having identical values in a particular

column. In the COMPANY table, for example, you might want to prevent two or more

people from having identical age.

For example, the following PostgreSQL statement creates a new table called COMPANY3

and adds five columns. Here, AGE column is set to UNIQUE, so that you cannot have two

records with same age −

CREATE TABLE COMPANY3(

ID INT PRIMARY KEY NOT NULL,

NAME TEXT NOT NULL,

AGE INT NOT NULL UNIQUE,

NOT NULL ConstraintNOT NULL Constraint

NOT NULL Constraint

ExampleExample

Example

UNIQUE ConstraintUNIQUE Constraint

UNIQUE Constraint

ExampleExample

Example

ADDRESS CHAR(50),

SALARY REAL DEFAULT 50000.00

);

The PRIMARY KEY constraint uniquely identifies each record in a database table. There can

be more UNIQUE columns, but only one primary key in a table. Primary keys are important

when designing the database tables. Primary keys are unique ids.

We use them to refer to table rows. Primary keys become foreign keys in other tables,

when creating relations among tables. Due to a 'longstanding coding oversight', primary

keys can be NULL in SQLite. This is not the case with other databases

A primary key is a field in a table, which uniquely identifies each row/record in a database

table. Primary keys must contain unique values. A primary key column cannot have NULL

values.

A table can have only one primary key, which may consist of single or multiple fields.

When multiple fields are used as a primary key, they are called a composite key.

If a table has a primary key defined on any field(s), then you cannot have two records

having the same value of that field(s).

You already have seen various examples above where we have created COMAPNY4 table

with ID as primary key −

CREATE TABLE COMPANY4(

ID INT PRIMARY KEY NOT NULL,

NAME TEXT NOT NULL,

AGE INT NOT NULL,

ADDRESS CHAR(50),

SALARY REAL

);

A foreign key constraint specifies that the values in a column (or a group of columns) must

match the values appearing in some row of another table. We say this maintains the

referential integrity between two related tables. They are called foreign keys because the

constraints are foreign; that is, outside the table. Foreign keys are sometimes called a

referencing key.

For example, the following PostgreSQL statement creates a new table called COMPANY5

and adds five columns.

PRIMARY KEY ConstraintPRIMARY KEY Constraint

PRIMARY KEY Constraint

ExampleExample

Example

FOREIGN KEY ConstraintFOREIGN KEY Constraint

FOREIGN KEY Constraint

ExampleExample

Example

CREATE TABLE COMPANY6(

ID INT PRIMARY KEY NOT NULL,

NAME TEXT NOT NULL,

AGE INT NOT NULL,

ADDRESS CHAR(50),

SALARY REAL

);

For example, the following PostgreSQL statement creates a new table called

DEPARTMENT1, which adds three columns. The column EMP_ID is the foreign key and

references the ID field of the table COMPANY6.

CREATE TABLE DEPARTMENT1(

ID INT PRIMARY KEY NOT NULL,

DEPT CHAR(50) NOT NULL,

EMP_ID INT references COMPANY6(ID)

);

The CHECK Constraint enables a condition to check the value being entered into a record.

If the condition evaluates to false, the record violates the constraint and is not entered into

the table.

For example, the following PostgreSQL statement creates a new table called COMPANY5

and adds five columns. Here, we add a CHECK with SALARY column, so that you cannot

have any SALARY as Zero.

CREATE TABLE COMPANY5(

ID INT PRIMARY KEY NOT NULL,

NAME TEXT NOT NULL,

AGE INT NOT NULL,

ADDRESS CHAR(50),

SALARY REAL CHECK(SALARY > 0)

);

Exclusion constraints ensure that if any two rows are compared on the specified columns

or expressions using the specified operators, at least one of these operator comparisons

will return false or null.

For example, the following PostgreSQL statement creates a new table called COMPANY7

and adds five columns. Here, we add an EXCLUDE constraint −

CREATE TABLE COMPANY7(

ID INT PRIMARY KEY NOT NULL,

CHECK ConstraintCHECK Constraint

CHECK Constraint

ExampleExample

Example

EXCLUSION ConstraintEXCLUSION Constraint

EXCLUSION Constraint

ExampleExample

Example

NAME TEXT,

AGE INT ,

ADDRESS CHAR(50),

SALARY REAL,

EXCLUDE USING gist

(NAME WITH =,

AGE WITH <>)

);

Here, USING gist is the type of index to build and use for enforcement.

You need to execute the command CREATE EXTENSION btree_gist, once per

database. This will install the btree_gist extension, which defines the exclusion

constraints on plain scalar data types.

As we have enforced the age has to be same, let us see this by inserting records to the

table −

INSERT INTO COMPANY7 VALUES(1, 'Paul', 32, 'California', 20000.00 );

INSERT INTO COMPANY7 VALUES(2, 'Paul', 32, 'Texas', 20000.00 );

INSERT INTO COMPANY7 VALUES(3, 'Allen', 42, 'California', 20000.00 );

For the first two INSERT statements, the records are added to the COMPANY7 table. For

the third INSERT statement, the following error is displayed −

ERROR: duplicate key value violates unique constraint "company7_pkey"

DETAIL: Key (id)=(3) already exists.

To remove a constraint you need to know its name. If the name is known, it is easy to

drop. Else, you need to find out the system-generated name. The psql command \d table

name can be helpful here. The general syntax is −

ALTER TABLE table_name DROP CONSTRAINT some_name;

PostgreSQL - JOINSPostgreSQL - JOINS

PostgreSQL - JOINS

The PostgreSQL Joins clause is used to combine records from two or more tables in a

database. A JOIN is a means for combining fields from two tables by using values common

to each.

Join Types in PostgreSQL are −

The CROSS JOIN

The INNER JOIN

The LEFT OUTER JOIN

Dropping ConstraintsDropping Constraints

Dropping Constraints

The RIGHT OUTER JOIN

The FULL OUTER JOIN

Before we proceed, let us consider two tables, COMPANY and DEPARTMENT. We already

have seen INSERT statements to populate COMPANY table. So just let us assume the list of

records available in COMPANY table −

----+-------+-----+-----------+--------+-----------

1 | Paul | 32 | California| 20000 | 2001-07-13

3 | Teddy | 23 | Norway | 20000 |

4 | Mark | 25 | Rich-Mond | 65000 | 2007-12-13

5 | David | 27 | Texas | 85000 | 2007-12-13

2 | Allen | 25 | Texas | | 2007-12-13

8 | Paul | 24 | Houston | 20000 | 2005-07-13

9 | James | 44 | Norway | 5000 | 2005-07-13

10 | James | 45 | Texas | 5000 | 2005-07-13

Another table is DEPARTMENT, has the following definition −

CREATE TABLE DEPARTMENT(

ID INT PRIMARY KEY NOT NULL,

DEPT CHAR(50) NOT NULL,

EMP_ID INT NOT NULL

);

Here is the list of INSERT statements to populate DEPARTMENT table −

INSERT INTO DEPARTMENT (ID, DEPT, EMP_ID)

VALUES (1, 'IT Billing', 1 );

INSERT INTO DEPARTMENT (ID, DEPT, EMP_ID)

VALUES (2, 'Engineering', 2 );

INSERT INTO DEPARTMENT (ID, DEPT, EMP_ID)

VALUES (3, 'Finance', 7 );

Finally, we have the following list of records available in DEPARTMENT table −

id | dept | emp_id

----+-------------+--------

1 | IT Billing | 1

2 | Engineering | 2

3 | Finance | 7

A CROSS JOIN matches every row of the first table with every row of the second table. If

the input tables have x and y columns, respectively, the resulting table will have x+y

columns. Because CROSS JOINs have the potential to generate extremely large tables,

care must be taken to use them only when appropriate.

The CROSS JOINThe CROSS JOIN

The CROSS JOIN

The following is the syntax of CROSS JOIN −

SELECT ... FROM table1 CROSS JOIN table2 ...

Based on the above tables, we can write a CROSS JOIN as follows −

testdb=# SELECT EMP_ID, NAME, DEPT FROM COMPANY CROSS JOIN DEPARTMENT;

The above given query will produce the following result −

emp_id| name | dept

------|-------|--------------

1 | Paul | IT Billing

1 | Teddy | IT Billing

1 | Mark | IT Billing

1 | David | IT Billing

1 | Allen | IT Billing

1 | Paul | IT Billing

1 | James | IT Billing

2 | Paul | Engineering

2 | Teddy | Engineering

2 | Mark | Engineering

2 | David | Engineering

2 | Allen | Engineering

2 | Paul | Engineering

2 | James | Engineering

7 | Paul | Finance

7 | Teddy | Finance

7 | Mark | Finance

7 | David | Finance

7 | Allen | Finance

7 | Paul | Finance

7 | James | Finance

A INNER JOIN creates a new result table by combining column values of two tables (table1

and table2) based upon the join-predicate. The query compares each row of table1 with

each row of table2 to find all pairs of rows, which satisfy the join-predicate. When the join-

predicate is satisfied, column values for each matched pair of rows of table1 and table2 are

combined into a result row.

The INNER JOINThe INNER JOIN

The INNER JOIN

An INNER JOIN is the most common type of join and is the default type of join. You can

use INNER keyword optionally.

The following is the syntax of INNER JOIN −

SELECT table1.column1, table2.column2...

FROM table1

INNER JOIN table2

ON table1.common_filed = table2.common_field;

Based on the above tables, we can write an INNER JOIN as follows −

testdb=# SELECT EMP_ID, NAME, DEPT FROM COMPANY INNER JOIN DEPARTMENT

ON COMPANY.ID = DEPARTMENT.EMP_ID;

The above given query will produce the following result −

emp_id | name | dept

--------+-------+------------

1 | Paul | IT Billing

2 | Allen | Engineering

The OUTER JOIN is an extension of the INNER JOIN. SQL standard defines three types of

OUTER JOINs: LEFT, RIGHT, and FULL and PostgreSQL supports all of these.

In case of LEFT OUTER JOIN, an inner join is performed first. Then, for each row in table

T1 that does not satisfy the join condition with any row in table T2, a joined row is added

with null values in columns of T2. Thus, the joined table always has at least one row for

each row in T1.

The following is the syntax of LEFT OUTER JOIN −

SELECT ... FROM table1 LEFT OUTER JOIN table2 ON conditional_expression ...

Based on the above tables, we can write an inner join as follows −

testdb=# SELECT EMP_ID, NAME, DEPT FROM COMPANY LEFT OUTER JOIN DEPARTMENT

ON COMPANY.ID = DEPARTMENT.EMP_ID;

The above given query will produce the following result −

emp_id | name | dept

--------+-------+------------

1 | Paul | IT Billing

2 | Allen | Engineering

| James |

| David |

The LEFT OUTER JOINThe LEFT OUTER JOIN

The LEFT OUTER JOIN

| Paul |

| Mark |

| Teddy |

| James |

First, an inner join is performed. Then, for each row in table T2 that does not satisfy the

join condition with any row in table T1, a joined row is added with null values in columns of

T1. This is the converse of a left join; the result table will always have a row for each row

in T2.

The following is the syntax of RIGHT OUTER JOIN −

SELECT ... FROM table1 RIGHT OUTER JOIN table2 ON conditional_expression ...

Based on the above tables, we can write an inner join as follows −

testdb=# SELECT EMP_ID, NAME, DEPT FROM COMPANY RIGHT OUTER JOIN DEPARTMENT

ON COMPANY.ID = DEPARTMENT.EMP_ID;

The above given query will produce the following result −

emp_id | name | dept

--------+-------+--------

1 | Paul | IT Billing

2 | Allen | Engineering

7 | | Finance

First, an inner join is performed. Then, for each row in table T1 that does not satisfy the

join condition with any row in table T2, a joined row is added with null values in columns of

T2. In addition, for each row of T2 that does not satisfy the join condition with any row in

T1, a joined row with null values in the columns of T1 is added.

The following is the syntax of FULL OUTER JOIN −

SELECT ... FROM table1 FULL OUTER JOIN table2 ON conditional_expression ...

Based on the above tables, we can write an inner join as follows −

testdb=# SELECT EMP_ID, NAME, DEPT FROM COMPANY FULL OUTER JOIN DEPARTMENT

ON COMPANY.ID = DEPARTMENT.EMP_ID;

The above given query will produce the following result −

emp_id | name | dept

--------+-------+---------------

The RIGHT OUTER JOINThe RIGHT OUTER JOIN

The RIGHT OUTER JOIN

The FULL OUTER JOINThe FULL OUTER JOIN

The FULL OUTER JOIN

1 | Paul | IT Billing

2 | Allen | Engineering

7 | | Finance

| James |

| David |

| Paul |

| Mark |

| Teddy |

| James |

PostgreSQL - UNIONS ClausePostgreSQL - UNIONS Clause

PostgreSQL - UNIONS Clause

The PostgreSQL UNION clause/operator is used to combine the results of two or more

SELECT statements without returning any duplicate rows.

To use UNION, each SELECT must have the same number of columns selected, the same

number of column expressions, the same data type, and have them in the same order but

they do not have to be the same length.

The basic syntax of UNION is as follows −

SELECT column1 [, column2 ]

FROM table1 [, table2 ]

[WHERE condition]

UNION

SELECT column1 [, column2 ]

FROM table1 [, table2 ]

[WHERE condition]

Here, given condition could be any given expression based on your requirement.

Consider the following two tables, (a) COMPANY table is as follows −

testdb=# SELECT * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

SyntaxSyntax

Syntax

ExampleExample

Example

7 | James | 24 | Houston | 10000

(7 rows)

(b) Another table is DEPARTMENT as follows −

testdb=# SELECT * from DEPARTMENT;

id | dept | emp_id

----+-------------+--------

1 | IT Billing | 1

2 | Engineering | 2

3 | Finance | 7

4 | Engineering | 3

5 | Finance | 4

6 | Engineering | 5

7 | Finance | 6

(7 rows)

Now let us join these two tables using SELECT statement along with UNION clause as

follows −

testdb=# SELECT EMP_ID, NAME, DEPT FROM COMPANY INNER JOIN DEPARTMENT

ON COMPANY.ID = DEPARTMENT.EMP_ID

UNION

SELECT EMP_ID, NAME, DEPT FROM COMPANY LEFT OUTER JOIN DEPARTMENT

ON COMPANY.ID = DEPARTMENT.EMP_ID;

This would produce the following result −

emp_id | name | dept

--------+-------+--------------

5 | David | Engineering

6 | Kim | Finance

2 | Allen | Engineering

3 | Teddy | Engineering

4 | Mark | Finance

1 | Paul | IT Billing

7 | James | Finance

(7 rows)

The UNION ALL operator is used to combine the results of two SELECT statements

including duplicate rows. The same rules that apply to UNION apply to the UNION ALL

operator as well.

The basic syntax of UNION ALL is as follows −

SELECT column1 [, column2 ]

FROM table1 [, table2 ]

The UNION ALL ClauseThe UNION ALL Clause

The UNION ALL Clause

SyntaxSyntax

Syntax

[WHERE condition]

UNION ALL

SELECT column1 [, column2 ]

FROM table1 [, table2 ]

[WHERE condition]

Here, given condition could be any given expression based on your requirement.

Now, let us join above-mentioned two tables in our SELECT statement as follows −

testdb=# SELECT EMP_ID, NAME, DEPT FROM COMPANY INNER JOIN DEPARTMENT

ON COMPANY.ID = DEPARTMENT.EMP_ID

UNION ALL

SELECT EMP_ID, NAME, DEPT FROM COMPANY LEFT OUTER JOIN DEPARTMENT

ON COMPANY.ID = DEPARTMENT.EMP_ID;

This would produce the following result −

emp_id | name | dept

--------+-------+--------------

1 | Paul | IT Billing

2 | Allen | Engineering

7 | James | Finance

3 | Teddy | Engineering

4 | Mark | Finance

5 | David | Engineering

6 | Kim | Finance

1 | Paul | IT Billing

2 | Allen | Engineering

7 | James | Finance

3 | Teddy | Engineering

4 | Mark | Finance

5 | David | Engineering

6 | Kim | Finance

(14 rows)

PostgreSQL - NULL ValuesPostgreSQL - NULL Values

PostgreSQL - NULL Values

The PostgreSQL NULL is the term used to represent a missing value. A NULL value in a

table is a value in a field that appears to be blank.

A field with a NULL value is a field with no value. It is very important to understand that a

NULL value is different from a zero value or a field that contains spaces.

ExampleExample

Example

The basic syntax of using NULL while creating a table is as follows −

CREATE TABLE COMPANY(

ID INT PRIMARY KEY NOT NULL,

NAME TEXT NOT NULL,

AGE INT NOT NULL,

ADDRESS CHAR(50),

SALARY REAL

);

Here, NOT NULL signifies that column should always accept an explicit value of the given

data type. There are two columns where we did not use NOT NULL. Hence, this means

these columns could be NULL.

A field with a NULL value is one that has been left blank during record creation.

The NULL value can cause problems when selecting data, because when comparing an

unknown value to any other value, the result is always unknown and not included in the

final results. Consider the following table, COMPANY having the following records −

ID NAME AGE ADDRESS SALARY

---------- ---------- ---------- ---------- ----------

1 Paul 32 California 20000.0

2 Allen 25 Texas 15000.0

3 Teddy 23 Norway 20000.0

4 Mark 25 Rich-Mond 65000.0

5 David 27 Texas 85000.0

6 Kim 22 South-Hall 45000.0

7 James 24 Houston 10000.0

Let us use the UPDATE statement to set few nullable values as NULL as follows −

testdb=# UPDATE COMPANY SET ADDRESS = NULL, SALARY = NULL where ID IN(6,7);

Now, COMPANY table should have the following records −

id | name | age | address | salary

----+-------+-----+-------------+--------

1 | Paul | 32 | California | 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | |

7 | James | 24 | |

(7 rows)

SyntaxSyntax

Syntax

ExampleExample

Example

Next, let us see the usage of IS NOT NULL operator to list down all the records where

SALARY is not NULL −

testdb=# SELECT ID, NAME, AGE, ADDRESS, SALARY

FROM COMPANY

WHERE SALARY IS NOT NULL;

The above given PostgreSQL statement will produce the following result −

id | name | age | address | salary

----+-------+-----+------------+--------

1 | Paul | 32 | California | 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

(5 rows)

The following is the usage of IS NULL operator which will list down all the records where

SALARY is NULL −

testdb=# SELECT ID, NAME, AGE, ADDRESS, SALARY

FROM COMPANY

WHERE SALARY IS NULL;

The above given PostgreSQL statement will produce the following result −

id | name | age | address | salary

----+-------+-----+---------+--------

6 | Kim | 22 | |

7 | James | 24 | |

(2 rows)

PostgreSQL - ALIAS SyntaxPostgreSQL - ALIAS Syntax

PostgreSQL - ALIAS Syntax

You can rename a table or a column temporarily by giving another name, which is known

as ALIAS. The use of table aliases means to rename a table in a particular PostgreSQL

statement. Renaming is a temporary change and the actual table name does not change in

the database.

The column aliases are used to rename a table's columns for the purpose of a particular

PostgreSQL query.

The basic syntax of table alias is as follows −

SyntaxSyntax

Syntax

SELECT column1, column2....

FROM table_name AS alias_name

WHERE [condition];

The basic syntax of column alias is as follows −

SELECT column_name AS alias_name

FROM table_name

WHERE [condition];

Consider the following two tables, (a) COMPANY table is as follows −

testdb=# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

(b) Another table is DEPARTMENT as follows −

id | dept | emp_id

----+--------------+--------

1 | IT Billing | 1

2 | Engineering | 2

3 | Finance | 7

4 | Engineering | 3

5 | Finance | 4

6 | Engineering | 5

7 | Finance | 6

(7 rows)

Now, following is the usage of TABLE ALIAS where we use C and D as aliases for

COMPANY and DEPARTMENT tables, respectively −

testdb=# SELECT C.ID, C.NAME, C.AGE, D.DEPT

FROM COMPANY AS C, DEPARTMENT AS D

WHERE C.ID = D.EMP_ID;

The above given PostgreSQL statement will produce the following result −

id | name | age | dept

----+-------+-----+------------

1 | Paul | 32 | IT Billing

2 | Allen | 25 | Engineering

ExampleExample

Example

7 | James | 24 | Finance

3 | Teddy | 23 | Engineering

4 | Mark | 25 | Finance

5 | David | 27 | Engineering

6 | Kim | 22 | Finance

(7 rows)

Let us see an example for the usage of COLUMN ALIAS where COMPANY_ID is an alias of

ID column and COMPANY_NAME is an alias of name column −

testdb=# SELECT C.ID AS COMPANY_ID, C.NAME AS COMPANY_NAME, C.AGE, D.DEPT

FROM COMPANY AS C, DEPARTMENT AS D

WHERE C.ID = D.EMP_ID;

The above given PostgreSQL statement will produce the following result −

company_id | company_name | age | dept

------------+--------------+-----+------------

1 | Paul | 32 | IT Billing

2 | Allen | 25 | Engineering

7 | James | 24 | Finance

3 | Teddy | 23 | Engineering

4 | Mark | 25 | Finance

5 | David | 27 | Engineering

6 | Kim | 22 | Finance

(7 rows)

PostgreSQL - TRIGGERSPostgreSQL - TRIGGERS

PostgreSQL - TRIGGERS

PostgreSQL Triggers are database callback functions, which are automatically

performed/invoked when a specified database event occurs.

The following are important points about PostgreSQL triggers −

PostgreSQL trigger can be specified to fire

Before the operation is attempted on a row (before constraints are checked

and the INSERT, UPDATE or DELETE is attempted)

After the operation has completed (after constraints are checked and the

INSERT, UPDATE, or DELETE has completed)

Instead of the operation (in the case of inserts, updates or deletes on a

view)

A trigger that is marked FOR EACH ROW is called once for every row that the

operation modifies. In contrast, a trigger that is marked FOR EACH STATEMENT

only executes once for any given operation, regardless of how many rows it

modifies.

Both, the WHEN clause and the trigger actions, may access elements of the row

being inserted, deleted or updated using references of the form NEW.column-

name and OLD.column-name, where column-name is the name of a column

from the table that the trigger is associated with.

If a WHEN clause is supplied, the PostgreSQL statements specified are only

executed for rows for which the WHEN clause is true. If no WHEN clause is

supplied, the PostgreSQL statements are executed for all rows.

If multiple triggers of the same kind are defined for the same event, they will be

fired in alphabetical order by name.

The BEFORE, AFTER or INSTEAD OF keyword determines when the trigger actions

will be executed relative to the insertion, modification or removal of the associated

row.

Triggers are automatically dropped when the table that they are associated with is

dropped.

The table to be modified must exist in the same database as the table or view to

which the trigger is attached and one must use just tablename, not

database.tablename.

A CONSTRAINT option when specified creates a constraint trigger. This is the same

as a regular trigger except that the timing of the trigger firing can be adjusted

using SET CONSTRAINTS. Constraint triggers are expected to raise an exception

when the constraints they implement are violated.

The basic syntax of creating a trigger is as follows −

CREATE TRIGGER trigger_name [BEFORE|AFTER|INSTEAD OF] event_name

ON table_name

[

-- Trigger logic goes here....

];

Here, event_name could be INSERT, DELETE, UPDATE, and TRUNCATE database

operation on the mentioned table table_name. You can optionally specify FOR EACH ROW

after table name.

The following is the syntax of creating a trigger on an UPDATE operation on one or more

specified columns of a table as follows −

SyntaxSyntax

Syntax

CREATE TRIGGER trigger_name [BEFORE|AFTER] UPDATE OF column_name

ON table_name

[

-- Trigger logic goes here....

];

Let us consider a case where we want to keep audit trial for every record being inserted in

COMPANY table, which we will create newly as follows (Drop COMPANY table if you already

have it).

testdb=# CREATE TABLE COMPANY(

ID INT PRIMARY KEY NOT NULL,

NAME TEXT NOT NULL,

AGE INT NOT NULL,

ADDRESS CHAR(50),

SALARY REAL

);

To keep audit trial, we will create a new table called AUDIT where log messages will be

inserted whenever there is an entry in COMPANY table for a new record −

testdb=# CREATE TABLE AUDIT(

EMP_ID INT NOT NULL,

ENTRY_DATE TEXT NOT NULL

);

Here, ID is the AUDIT record ID, and EMP_ID is the ID, which will come from COMPANY

table, and DATE will keep timestamp when the record will be created in COMPANY table. So

now, let us create a trigger on COMPANY table as follows −

testdb=# CREATE TRIGGER example_trigger AFTER INSERT ON COMPANY

FOR EACH ROW EXECUTE PROCEDURE auditlogfunc();

Where auditlogfunc() is a PostgreSQL procedure and has the following definition −

CREATE OR REPLACE FUNCTION auditlogfunc() RETURNS TRIGGER AS $example_table$

BEGIN

INSERT INTO AUDIT(EMP_ID, ENTRY_DATE) VALUES (new.ID, current_timestamp);

RETURN NEW;

END;

$example_table$ LANGUAGE plpgsql;

Now, we will start the actual work. Let us start inserting record in COMPANY table which

should result in creating an audit log record in AUDIT table. So let us create one record in

COMPANY table as follows −

testdb=# INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)

VALUES (1, 'Paul', 32, 'California', 20000.00 );

ExampleExample

Example

This will create one record in COMPANY table, which is as follows −

id | name | age | address | salary

----+------+-----+--------------+--------

1 | Paul | 32 | California | 20000

Same time, one record will be created in AUDIT table. This record is the result of a trigger,

which we have created on INSERT operation on COMPANY table. Similarly, you can create

your triggers on UPDATE and DELETE operations based on your requirements.

emp_id | entry_date

--------+-------------------------------

1 | 2013-05-05 15:49:59.968+05:30

(1 row)

You can list down all the triggers in the current database from pg_trigger table as follows

−

testdb=# SELECT * FROM pg_trigger;

The above given PostgreSQL statement will list down all triggers.

If you want to list the triggers on a particular table, then use AND clause with table name

as follows −

The above given PostgreSQL statement will also list down only one entry as follows −

tgname

-----------------

example_trigger

(1 row)

The following is the DROP command, which can be used to drop an existing trigger −

testdb=# DROP TRIGGER trigger_name;

PostgreSQL - INDEXESPostgreSQL - INDEXES

PostgreSQL - INDEXES

Indexes are special lookup tables that the database search engine can use to speed up

data retrieval. Simply put, an index is a pointer to data in a table. An index in a database

is very similar to an index in the back of a book.

testdb=# SELECT tgname FROM pg_trigger, pg_class WHERE tgrelid=pg_class.oid AND relname='company'

Listing TRIGGERSListing TRIGGERS

Listing TRIGGERS

Dropping TRIGGERSDropping TRIGGERS

Dropping TRIGGERS

For example, if you want to reference all pages in a book that discusses a certain topic,

you have to first refer to the index, which lists all topics alphabetically and then refer to

one or more specific page numbers.

An index helps to speed up SELECT queries and WHERE clauses; however, it slows down

data input, with UPDATE and INSERT statements. Indexes can be created or dropped with

no effect on the data.

Creating an index involves the CREATE INDEX statement, which allows you to name the

index, to specify the table and which column or columns to index, and to indicate whether

the index is in ascending or descending order.

Indexes can also be unique, similar to the UNIQUE constraint, in that the index prevents

duplicate entries in the column or combination of columns on which there's an index.

The basic syntax of CREATE INDEX is as follows −

CREATE INDEX index_name ON table_name;

PostgreSQL provides several index types: B-tree, Hash, GiST, SP-GiST and GIN. Each

Index type uses a different algorithm that is best suited to different types of queries. By

default, the CREATE INDEX command creates B-tree indexes, which fit the most common

situations.

A single-column index is one that is created based on only one table column. The basic

syntax is as follows −

CREATE INDEX index_name

ON table_name (column_name);

A multicolumn index is defined on more than one column of a table. The basic syntax is as

follows −

CREATE INDEX index_name

ON table_name (column1_name, column2_name);

Whether to create a single-column index or a multicolumn index, take into consideration

the column(s) that you may use very frequently in a query's WHERE clause as filter

conditions.

The CREATE INDEX CommandThe CREATE INDEX Command

The CREATE INDEX Command

Index TypesIndex Types

Index Types

Single-Column IndexesSingle-Column Indexes

Single-Column Indexes

Multicolumn IndexesMulticolumn Indexes

Multicolumn Indexes

Should there be only one column used, a single-column index should be the choice. Should

there be two or more columns that are frequently used in the WHERE clause as filters, the

multicolumn index would be the best choice.

Unique indexes are used not only for performance, but also for data integrity. A unique

index does not allow any duplicate values to be inserted into the table. The basic syntax is

as follows −

CREATE UNIQUE INDEX index_name

on table_name (column_name);

A partial index is an index built over a subset of a table; the subset is defined by a

conditional expression (called the predicate of the partial index). The index contains

entries only for those table rows that satisfy the predicate. The basic syntax is as follows −

CREATE INDEX index_name

on table_name (conditional_expression);

Implicit indexes are indexes that are automatically created by the database server when

an object is created. Indexes are automatically created for primary key constraints and

unique constraints.

The following is an example where we will create an index on COMPANY table for salary

column −

# CREATE INDEX salary_index ON COMPANY (salary);

Now, let us list down all the indices available on COMPANY table using \d company

command.

# \d company

This will produce the following result, where company_pkey is an implicit index, which got

created when the table was created.

Table "public.company"

Column | Type | Modifiers

---------+---------------+-----------

id | integer | not null

name | text | not null

age | integer | not null

Unique IndexesUnique Indexes

Unique Indexes

Partial IndexesPartial Indexes

Partial Indexes

Implicit IndexesImplicit Indexes

Implicit Indexes

ExampleExample

Example

address | character(50) |

salary | real |

Indexes:

"company_pkey" PRIMARY KEY, btree (id)

"salary_index" btree (salary)

You can list down the entire indexes database wide using the \di command −

An index can be dropped using PostgreSQL DROP command. Care should be taken when

dropping an index because performance may be slowed or improved.

The basic syntax is as follows −

DROP INDEX index_name;

You can use following statement to delete previously created index −

# DROP INDEX salary_index;

Although indexes are intended to enhance a database's performance, there are times when

they should be avoided. The following guidelines indicate when the use of an index should

be reconsidered −

Indexes should not be used on small tables.

Tables that have frequent, large batch update or insert operations.

Indexes should not be used on columns that contain a high number of NULL

values.

Columns that are frequently manipulated should not be indexed.

PostgreSQL - ALTER TABLE CommandPostgreSQL - ALTER TABLE Command

PostgreSQL - ALTER TABLE Command

The PostgreSQL ALTER TABLE command is used to add, delete or modify columns in an

existing table.

You would also use ALTER TABLE command to add and drop various constraints on an

existing table.

The basic syntax of ALTER TABLE to add a new column in an existing table is as follows −

ALTER TABLE table_name ADD column_name datatype;

The DROP INDEX CommandThe DROP INDEX Command

The DROP INDEX Command

When Should Indexes be Avoided?When Should Indexes be Avoided?

When Should Indexes be Avoided?

SyntaxSyntax

Syntax

The basic syntax of ALTER TABLE to DROP COLUMN in an existing table is as follows −

ALTER TABLE table_name DROP COLUMN column_name;

The basic syntax of ALTER TABLE to change the DATA TYPE of a column in a table is as

follows −

ALTER TABLE table_name ALTER COLUMN column_name TYPE datatype;

The basic syntax of ALTER TABLE to add a NOT NULL constraint to a column in a table is

as follows −

ALTER TABLE table_name MODIFY column_name datatype NOT NULL;

The basic syntax of ALTER TABLE to ADD UNIQUE CONSTRAINT to a table is as follows

−

ALTER TABLE table_name

ADD CONSTRAINT MyUniqueConstraint UNIQUE(column1, column2...);

The basic syntax of ALTER TABLE to ADD CHECK CONSTRAINT to a table is as follows −

ALTER TABLE table_name

ADD CONSTRAINT MyUniqueConstraint CHECK (CONDITION);

The basic syntax of ALTER TABLE to ADD PRIMARY KEY constraint to a table is as follows

−

ALTER TABLE table_name

ADD CONSTRAINT MyPrimaryKey PRIMARY KEY (column1, column2...);

The basic syntax of ALTER TABLE to DROP CONSTRAINT from a table is as follows −

ALTER TABLE table_name

DROP CONSTRAINT MyUniqueConstraint;

If you are using MySQL, the code is as follows −

ALTER TABLE table_name

DROP INDEX MyUniqueConstraint;

The basic syntax of ALTER TABLE to DROP PRIMARY KEY constraint from a table is as

follows −

ALTER TABLE table_name

DROP CONSTRAINT MyPrimaryKey;

If you are using MySQL, the code is as follows −

ALTER TABLE table_name

DROP PRIMARY KEY;

Consider our COMPANY table has the following records −

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

The following is the example to ADD a new column in an existing table −

testdb=# ALTER TABLE COMPANY ADD GENDER char(1);

Now, COMPANY table is changed and the following would be the output from SELECT

statement −

----+-------+-----+-------------+--------+--------

1 | Paul | 32 | California | 20000 |

2 | Allen | 25 | Texas | 15000 |

3 | Teddy | 23 | Norway | 20000 |

4 | Mark | 25 | Rich-Mond | 65000 |

5 | David | 27 | Texas | 85000 |

6 | Kim | 22 | South-Hall | 45000 |

7 | James | 24 | Houston | 10000 |

(7 rows)

The following is the example to DROP gender column from existing table −

testdb=# ALTER TABLE COMPANY DROP GENDER;

Now, COMPANY table is changed and the following would be the output from SELECT

statement −

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

PostgreSQL - TRUNCATE TABLE CommandPostgreSQL - TRUNCATE TABLE Command

PostgreSQL - TRUNCATE TABLE Command

The PostgreSQL TRUNCATE TABLE command is used to delete complete data from an

existing table. You can also use DROP TABLE command to delete complete table but it

ExampleExample

Example

would remove complete table structure from the database and you would need to re-

create this table once again if you wish to store some data.

It has the same effect as DELETE on each table, but since it does not actually scan the

tables, it is faster. Furthermore, it reclaims disk space immediately, rather than requiring a

subsequent VACUUM operation. This is most useful on large tables.

The basic syntax of TRUNCATE TABLE is as follows −

TRUNCATE TABLE table_name;

Consider the COMPANY table has the following records −

id | name | age | address | salary

----+-------+-----+------------+--------

1 | Paul | 32 | California | 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

(7 rows)

The following is the example to truncate −

testdb=# TRUNCATE TABLE COMPANY;

Now, COMPANY table is truncated and the following would be the output of SELECT

statement −

testdb=# SELECT * FROM CUSTOMERS;

id | name | age | address | salary

----+------+-----+---------+--------

(0 rows)

PostgreSQL - VIEWSPostgreSQL - VIEWS

PostgreSQL - VIEWS

Views are pseudo-tables. That is, they are not real tables; nevertheless appear as ordinary

tables to SELECT. A view can represent a subset of a real table, selecting certain columns

or certain rows from an ordinary table. A view can even represent joined tables. Because

views are assigned separate permissions, you can use them to restrict table access so that

the users see only specific rows or columns of a table.

SyntaxSyntax

Syntax

ExampleExample

Example

A view can contain all rows of a table or selected rows from one or more tables. A view can

be created from one or many tables, which depends on the written PostgreSQL query to

create a view.

Views, which are kind of virtual tables, allow users to do the following −

Structure data in a way that users or classes of users find natural or intuitive.

Restrict access to the data such that a user can only see limited data instead of

complete table.

Summarize data from various tables, which can be used to generate reports.

Since views are not ordinary tables, you may not be able to execute a DELETE, INSERT, or

UPDATE statement on a view. However, you can create a RULE to correct this problem of

using DELETE, INSERT or UPDATE on a view.

The PostgreSQL views are created using the CREATE VIEW statement. The PostgreSQL

views can be created from a single table, multiple tables, or another view.

The basic CREATE VIEW syntax is as follows −

CREATE [TEMP | TEMPORARY] VIEW view_name AS

SELECT column1, column2.....

FROM table_name

WHERE [condition];

You can include multiple tables in your SELECT statement in very similar way as you use

them in normal PostgreSQL SELECT query. If the optional TEMP or TEMPORARY keyword is

present, the view will be created in the temporary space. Temporary views are

automatically dropped at the end of the current session.

Consider, the COMPANY table is having the following records −

id | name | age | address | salary

----+-------+-----+------------+--------

1 | Paul | 32 | California | 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

Now, following is an example to create a view from COMPANY table. This view would be

used to have only few columns from COMPANY table −

Creating ViewsCreating Views

Creating Views

ExampleExample

Example

testdb=# CREATE VIEW COMPANY_VIEW AS

SELECT ID, NAME, AGE

FROM COMPANY;

Now, you can query COMPANY_VIEW in a similar way as you query an actual table.

Following is the example −

testdb=# SELECT * FROM COMPANY_VIEW;

This would produce the following result −

id | name | age

----+-------+-----

1 | Paul | 32

2 | Allen | 25

3 | Teddy | 23

4 | Mark | 25

5 | David | 27

6 | Kim | 22

7 | James | 24

(7 rows)

To drop a view, simply use the DROP VIEW statement with the view_name. The basic

DROP VIEW syntax is as follows −

testdb=# DROP VIEW view_name;

The following command will delete COMPANY_VIEW view, which we created in the last

section −

testdb=# DROP VIEW COMPANY_VIEW;

PostgreSQL - TRANSACTIONSPostgreSQL - TRANSACTIONS

PostgreSQL - TRANSACTIONS

A transaction is a unit of work that is performed against a database. Transactions are units

or sequences of work accomplished in a logical order, whether in a manual fashion by a

user or automatically by some sort of a database program.

A transaction is the propagation of one or more changes to the database. For example, if

you are creating a record, updating a record, or deleting a record from the table, then you

are performing transaction on the table. It is important to control transactions to ensure

data integrity and to handle database errors.

Practically, you will club many PostgreSQL queries into a group and you will execute all of

them together as a part of a transaction.

Dropping ViewsDropping Views

Dropping Views

Transactions have the following four standard properties, usually referred to by the

acronym ACID −

Atomicity − Ensures that all operations within the work unit are completed

successfully; otherwise, the transaction is aborted at the point of failure and

previous operations are rolled back to their former state.

Consistency − Ensures that the database properly changes states upon a

successfully committed transaction.

Isolation − Enables transactions to operate independently of and transparent to

each other.

Durability − Ensures that the result or effect of a committed transaction persists

in case of a system failure.

The following commands are used to control transactions −

BEGIN TRANSACTION − To start a transaction.

COMMIT − To save the changes, alternatively you can use END TRANSACTION

command.

ROLLBACK − To rollback the changes.

Transactional control commands are only used with the DML commands INSERT, UPDATE

and DELETE only. They cannot be used while creating tables or dropping them because

these operations are automatically committed in the database.

Transactions can be started using BEGIN TRANSACTION or simply BEGIN command. Such

transactions usually persist until the next COMMIT or ROLLBACK command is encountered.

But a transaction will also ROLLBACK if the database is closed or if an error occurs.

The following is the simple syntax to start a transaction −

BEGIN;

BEGIN TRANSACTION;

Properties of TransactionsProperties of Transactions

Properties of Transactions

Transaction ControlTransaction Control

Transaction Control

The BEGIN TRANSACTION CommandThe BEGIN TRANSACTION Command

The BEGIN TRANSACTION Command

The COMMIT CommandThe COMMIT Command

The COMMIT Command

The COMMIT command is the transactional command used to save changes invoked by a

transaction to the database.

The COMMIT command saves all transactions to the database since the last COMMIT or

ROLLBACK command.

The syntax for COMMIT command is as follows −

COMMIT;

END TRANSACTION;

The ROLLBACK command is the transactional command used to undo transactions that

have not already been saved to the database.

The ROLLBACK command can only be used to undo transactions since the last COMMIT or

ROLLBACK command was issued.

The syntax for ROLLBACK command is as follows −

ROLLBACK;

Consider the COMPANY table is having the following records −

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

Now, let us start a transaction and delete records from the table having age = 25 and

finally we use ROLLBACK command to undo all the changes.

testdb=# BEGIN;

DELETE FROM COMPANY WHERE AGE = 25;

ROLLBACK;

If you will check COMPANY table is still having the following records −

id | name | age | address | salary

----+-------+-----+-----------+--------

The ROLLBACK CommandThe ROLLBACK Command

The ROLLBACK Command

ExampleExample

Example

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

Now, let us start another transaction and delete records from the table having age = 25

and finally we use COMMIT command to commit all the changes.

testdb=# BEGIN;

DELETE FROM COMPANY WHERE AGE = 25;

COMMIT;

If you will check the COMPANY table, it still has the following records −

id | name | age | address | salary

----+-------+-----+------------+--------

1 | Paul | 32 | California | 20000

3 | Teddy | 23 | Norway | 20000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

(5 rows)

PostgreSQL - LOCKSPostgreSQL - LOCKS

PostgreSQL - LOCKS

Locks or Exclusive Locks or Write Locks prevent users from modifying a row or an entire

table. Rows modified by UPDATE and DELETE are then exclusively locked automatically for

the duration of the transaction. This prevents other users from changing the row until the

transaction is either committed or rolled back.

The only time when users must wait for other users is when they are trying to modify the

same row. If they modify different rows, no waiting is necessary. SELECT queries never

have to wait.

The database performs locking automatically. In certain cases, however, locking must be

controlled manually. Manual locking can be done by using the LOCK command. It allows

specification of a transaction's lock type and scope.

The basic syntax for LOCK command is as follows −

LOCK [ TABLE ]

name

lock_mode

Syntax for LOCK commandSyntax for LOCK command

Syntax for LOCK command

name − The name (optionally schema-qualified) of an existing table to lock. If

ONLY is specified before the table name, only that table is locked. If ONLY is not

specified, the table and all its descendant tables (if any) are locked.

lock_mode − The lock mode specifies which locks this lock conflicts with. If no

lock mode is specified, then ACCESS EXCLUSIVE, the most restrictive mode, is

used. Possible values are: ACCESS SHARE, ROW SHARE, ROW EXCLUSIVE, SHARE

UPDATE EXCLUSIVE, SHARE, SHARE ROW EXCLUSIVE, EXCLUSIVE, ACCESS

EXCLUSIVE.

Once obtained, the lock is held for the remainder of the current transaction. There is

no UNLOCK TABLE command; locks are always released at the transaction end.

Deadlocks can occur when two transactions are waiting for each other to finish their

operations. While PostgreSQL can detect them and end them with a ROLLBACK, deadlocks

can still be inconvenient. To prevent your applications from running into this problem,

make sure to design them in such a way that they will lock objects in the same order.

PostgreSQL provides means for creating locks that have application-defined meanings.

These are called advisory locks. As the system does not enforce their use, it is up to the

application to use them correctly. Advisory locks can be useful for locking strategies that

are an awkward fit for the MVCC model.

For example, a common use of advisory locks is to emulate pessimistic locking strategies

typical of the so-called "flat file" data management systems. While a flag stored in a table

could be used for the same purpose, advisory locks are faster, avoid table bloat, and are

automatically cleaned up by the server at the end of the session.

Consider the table COMPANY having records as follows −

testdb# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

DeadLocksDeadLocks

DeadLocks

Advisory LocksAdvisory Locks

Advisory Locks

ExampleExample

Example

The following example locks the COMPANY table within the testdb database in ACCESS

EXCLUSIVE mode. The LOCK statement works only in a transaction mode −

testdb=#BEGIN;

LOCK TABLE company1 IN ACCESS EXCLUSIVE MODE;

The above given PostgreSQL statement will produce the following result −

LOCK TABLE

The above message indicates that the table is locked until the transaction ends and to

finish the transaction you will have to either rollback or commit the transaction.

PostgreSQL - Sub QueriesPostgreSQL - Sub Queries

PostgreSQL - Sub Queries

A subquery or Inner query or Nested query is a query within another PostgreSQL query

and embedded within the WHERE clause.

A subquery is used to return data that will be used in the main query as a condition to

further restrict the data to be retrieved.

Subqueries can be used with the SELECT, INSERT, UPDATE and DELETE statements along

with the operators like =, <, >, >=, <=, IN, etc.

There are a few rules that subqueries must follow −

Subqueries must be enclosed within parentheses.

A subquery can have only one column in the SELECT clause, unless multiple

columns are in the main query for the subquery to compare its selected columns.

An ORDER BY cannot be used in a subquery, although the main query can use an

ORDER BY. The GROUP BY can be used to perform the same function as the ORDER

BY in a subquery.

Subqueries that return more than one row can only be used with multiple value

operators, such as the IN, EXISTS, NOT IN, ANY/SOME, ALL operator.

The BETWEEN operator cannot be used with a subquery; however, the BETWEEN

can be used within the subquery.

Subqueries are most frequently used with the SELECT statement. The basic syntax is as

follows −

SELECT column_name [, column_name ]

FROM table1 [, table2 ]

WHERE column_name OPERATOR

(SELECT column_name [, column_name ]

Subqueries with the SELECT StatementSubqueries with the SELECT Statement

Subqueries with the SELECT Statement

FROM table1 [, table2 ]

[WHERE])

Consider the COMPANY table having the following records −

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

Now, let us check the following sub-query with SELECT statement −

testdb=# SELECT *

FROM COMPANY

WHERE ID IN (SELECT ID

FROM COMPANY

WHERE SALARY > 45000) ;

This would produce the following result −

id | name | age | address | salary

----+-------+-----+-------------+--------

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

(2 rows)

Subqueries also can be used with INSERT statements. The INSERT statement uses the

data returned from the subquery to insert into another table. The selected data in the

subquery can be modified with any of the character, date, or number functions.

The basic syntax is as follows −

INSERT INTO table_name [ (column1 [, column2 ]) ]

SELECT [ *|column1 [, column2 ] ]

FROM table1 [, table2 ]

[ WHERE VALUE OPERATOR ]

Consider a table COMPANY_BKP, with similar structure as COMPANY table and can be

created using the same CREATE TABLE using COMPANY_BKP as the table name. Now, to

ExampleExample

Example

Subqueries with the INSERT StatementSubqueries with the INSERT Statement

Subqueries with the INSERT Statement

ExampleExample

Example

copy complete COMPANY table into COMPANY_BKP, following is the syntax −

testdb=# INSERT INTO COMPANY_BKP

SELECT * FROM COMPANY

WHERE ID IN (SELECT ID

FROM COMPANY) ;

The subquery can be used in conjunction with the UPDATE statement. Either single or

multiple columns in a table can be updated when using a subquery with the UPDATE

statement.

The basic syntax is as follows −

UPDATE table

SET column_name = new_value

[ WHERE OPERATOR [ VALUE ]

(SELECT COLUMN_NAME

FROM TABLE_NAME)

[ WHERE) ]

Assuming, we have COMPANY_BKP table available, which is backup of the COMPANY table.

The following example updates SALARY by 0.50 times in the COMPANY table for all the

customers, whose AGE is greater than or equal to 27 −

testdb=# UPDATE COMPANY

SET SALARY = SALARY * 0.50

WHERE AGE IN (SELECT AGE FROM COMPANY_BKP

WHERE AGE >= 27 );

This would affect two rows and finally the COMPANY table would have the following records

−

id | name | age | address | salary

----+-------+-----+-------------+--------

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

1 | Paul | 32 | California | 10000

5 | David | 27 | Texas | 42500

(7 rows)

Subqueries with the UPDATE StatementSubqueries with the UPDATE Statement

Subqueries with the UPDATE Statement

ExampleExample

Example

Subqueries with the DELETE StatementSubqueries with the DELETE Statement

Subqueries with the DELETE Statement

The subquery can be used in conjunction with the DELETE statement like with any other

statements mentioned above.

The basic syntax is as follows −

DELETE FROM TABLE_NAME

[ WHERE OPERATOR [ VALUE ]

(SELECT COLUMN_NAME

FROM TABLE_NAME)

[ WHERE) ]

Assuming, we have COMPANY_BKP table available, which is a backup of the COMPANY

table.

The following example deletes records from the COMPANY table for all the customers,

whose AGE is greater than or equal to 27 −

testdb=# DELETE FROM COMPANY

WHERE AGE IN (SELECT AGE FROM COMPANY_BKP

WHERE AGE > 27 );

This would affect two rows and finally the COMPANY table would have the following records

−

id | name | age | address | salary

----+-------+-----+-------------+--------

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

5 | David | 27 | Texas | 42500

(6 rows)

PostgreSQL - AUTO INCREMENTPostgreSQL - AUTO INCREMENT

PostgreSQL - AUTO INCREMENT

PostgreSQL has the data types smallserial, serial and bigserial; these are not true types,

but merely a notational convenience for creating unique identifier columns. These are

similar to AUTO_INCREMENT property supported by some other databases.

If you wish a serial column to have a unique constraint or be a primary key, it must now be

specified, just like any other data type.

The type name serial creates an integer columns. The type name bigserial creates a bigint

column. bigserial should be used if you anticipate the use of more than 231 identifiers over

the lifetime of the table. The type name smallserial creates a smallint column.

ExampleExample

Example

The basic usage of SERIAL dataype is as follows −

CREATE TABLE tablename (

colname SERIAL

);

Consider the COMPANY table to be created as follows −

testdb=# CREATE TABLE COMPANY(

ID SERIAL PRIMARY KEY,

NAME TEXT NOT NULL,

AGE INT NOT NULL,

ADDRESS CHAR(50),

SALARY REAL

);

Now, insert the following records into table COMPANY −

INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)

VALUES ( 'Paul', 32, 'California', 20000.00 );

INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)

VALUES ('Allen', 25, 'Texas', 15000.00 );

INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)

VALUES ('Teddy', 23, 'Norway', 20000.00 );

INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)

VALUES ( 'Mark', 25, 'Rich-Mond ', 65000.00 );

INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)

VALUES ( 'David', 27, 'Texas', 85000.00 );

INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)

VALUES ( 'Kim', 22, 'South-Hall', 45000.00 );

INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)

VALUES ( 'James', 24, 'Houston', 10000.00 );

This will insert seven tuples into the table COMPANY and COMPANY will have the following

records −

id | name | age | address | salary

----+-------+-----+------------+--------

1 | Paul | 32 | California | 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

SyntaxSyntax

Syntax

ExampleExample

Example

6 | Kim | 22 | South-Hall | 45000

7 | James | 24 | Houston | 10000

PostgreSQL - PRIVILEGESPostgreSQL - PRIVILEGES

PostgreSQL - PRIVILEGES

Whenever an object is created in a database, an owner is assigned to it. The owner is

usually the one who executed the creation statement. For most kinds of objects, the initial

state is that only the owner (or a superuser) can modify or delete the object. To allow

other roles or users to use it, privileges or permission must be granted.

Different kinds of privileges in PostgreSQL are −

SELECT,

INSERT,

UPDATE,

DELETE,

TRUNCATE,

REFERENCES,

TRIGGER,

CREATE,

CONNECT,

TEMPORARY,

EXECUTE, and

USAGE

Depending on the type of the object (table, function, etc.,), privileges are applied to the

object. To assign privileges to the users, the GRANT command is used.

Basic syntax for GRANT command is as follows −

GRANT privilege [, ...]

ON object [, ...]

TO { PUBLIC | GROUP group | username }

privilege − values could be: SELECT, INSERT, UPDATE, DELETE, RULE, ALL.

object − The name of an object to which to grant access. The possible objects

are: table, view, sequence

PUBLIC − A short form representing all users.

GROUP group − A group to whom to grant privileges.

Syntax for GRANTSyntax for GRANT

Syntax for GRANT

username − The name of a user to whom to grant privileges. PUBLIC is a short

form representing all users.

The privileges can be revoked using the REVOKE command.

Basic syntax for REVOKE command is as follows −

REVOKE privilege [, ...]

ON object [, ...]

FROM { PUBLIC | GROUP groupname | username }

privilege − values could be: SELECT, INSERT, UPDATE, DELETE, RULE, ALL.

object − The name of an object to which to grant access. The possible objects

are: table, view, sequence

PUBLIC − A short form representing all users.

GROUP group − A group to whom to grant privileges.

username − The name of a user to whom to grant privileges. PUBLIC is a short

form representing all users.

To understand the privileges, let us first create a USER as follows −

testdb=# CREATE USER manisha WITH PASSWORD 'password';

CREATE ROLE

The message CREATE ROLE indicates that the USER "manisha" is created.

Consider the table COMPANY having records as follows −

testdb# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

Next, let us grant all privileges on a table COMPANY to the user "manisha" as follows −

Syntax for REVOKESyntax for REVOKE

Syntax for REVOKE

ExampleExample

Example

testdb=# GRANT ALL ON COMPANY TO manisha;

GRANT

The message GRANT indicates that all privileges are assigned to the USER.

Next, let us revoke the privileges from the USER "manisha" as follows −

testdb=# REVOKE ALL ON COMPANY FROM manisha;

REVOKE

The message REVOKE indicates that all privileges are revoked from the USER.

You can even delete the user as follows −

testdb=# DROP USER manisha;

DROP ROLE

The message DROP ROLE indicates USER ‘Manisha’ is deleted from the database.

PostgreSQL - DATE/TIME Functions andPostgreSQL - DATE/TIME Functions and

PostgreSQL - DATE/TIME Functions and

OperatorsOperators

Operators

We had discussed about the Date/Time data types in the chapter Data Types . Now, let

us see the Date/Time operators and Functions.

The following table lists the behaviors of the basic arithmetic operators −

Operator Example Result

+ date '2001-09-28' + integer '7' date '2001-10-05'

+ date '2001-09-28' + interval '1 hour' timestamp '2001-09-28 01:00:00'

+ date '2001-09-28' + time '03:00' timestamp '2001-09-28 03:00:00'

+ interval '1 day' + interval '1 hour' interval '1 day 01:00:00'

+timestamp '2001-09-28 01:00' + interval '23

hours' timestamp '2001-09-29 00:00:00'

+ time '01:00' + interval '3 hours' time '04:00:00'

- - interval '23 hours' interval '-23:00:00'

- date '2001-10-01' - date '2001-09-28' integer '3' (days)

- date '2001-10-01' - integer '7' date '2001-09-24'

- date '2001-09-28' - interval '1 hour' timestamp '2001-09-27 23:00:00'

- time '05:00' - time '03:00' interval '02:00:00'

- time '05:00' - interval '2 hours' time '03:00:00'

-timestamp '2001-09-28 23:00' - interval '23

hours' timestamp '2001-09-28 00:00:00'

- interval '1 day' - interval '1 hour' interval '1 day -01:00:00'

-timestamp '2001-09-29 03:00' - timestamp

'2001-09-27 12:00' interval '1 day 15:00:00'

* 900 * interval '1 second' interval '00:15:00'

* 21 * interval '1 day' interval '21 days'

* double precision '3.5' * interval '1 hour' interval '03:30:00'

/ interval '1 hour' / double precision '1.5' interval '00:40:00'

The following is the list of all important Date and Time related functions available.

S. No. Function & Description

AGE()

Subtract arguments

CURRENT DATE/TIME()

Current date and time

DATE_PART()

Get subfield (equivalent to extract)

EXTRACT()

Get subfield

ISFINITE()

Test for finite date, time and interval (not +/-infinity)

JUSTIFY

Adjust interval

S. No. Function & Description

AGE(timestamp, timestamp), AGE(timestamp)AGE(timestamp, timestamp), AGE(timestamp)

AGE(timestamp, timestamp), AGE(timestamp)

AGE(timestamp, timestamp)

When invoked with the TIMESTAMP form of the second argument, AGE()

subtract arguments, producing a "symbolic" result that uses years and months

and is of type INTERVAL.

AGE(timestamp)

When invoked with only the TIMESTAMP as argument, AGE() subtracts from

the current_date (at midnight).

Example of the function AGE(timestamp, timestamp) is −

testdb=# SELECT AGE(timestamp '2001-04-10', timestamp '1957-06-13');

The above given PostgreSQL statement will produce the following result −

age

-------------------------

43 years 9 mons 27 days

Example of the function AGE(timestamp) is −

testdb=# select age(timestamp '1957-06-13');

The above given PostgreSQL statement will produce the following result −

age

--------------------------

55 years 10 mons 22 days

PostgreSQL provides a number of functions that return values related to the current date

and time. Following are some functions −

S. No. Function & Description

CURRENT_DATE

Delivers current date.

CURRENT_TIME

Delivers values with time zone.

3CURRENT_TIMESTAMP

CURRENT DATE/TIME()CURRENT DATE/TIME()

CURRENT DATE/TIME()

Delivers values with time zone.

CURRENT_TIME(precision)

Optionally takes a precision parameter, which causes the result to be rounded

to that many fractional digits in the seconds field.

CURRENT_TIMESTAMP(precision)

Optionally takes a precision parameter, which causes the result to be rounded

to that many fractional digits in the seconds field.

LOCALTIME

Delivers values without time zone.

LOCALTIMESTAMP

Delivers values without time zone.

LOCALTIME(precision)

Optionally takes a precision parameter, which causes the result to be rounded

to that many fractional digits in the seconds field.

LOCALTIMESTAMP(precision)

Optionally takes a precision parameter, which causes the result to be rounded

to that many fractional digits in the seconds field.

Examples using the functions from the table above −

testdb=# SELECT CURRENT_TIME;

timetz

--------------------

08:01:34.656+05:30

(1 row)

testdb=# SELECT CURRENT_DATE;

date

------------

2013-05-05

(1 row)

testdb=# SELECT CURRENT_TIMESTAMP;

now

-------------------------------

2013-05-05 08:01:45.375+05:30

(1 row)

testdb=# SELECT CURRENT_TIMESTAMP(2);

timestamptz

------------------------------

2013-05-05 08:01:50.89+05:30

(1 row)

testdb=# SELECT LOCALTIMESTAMP;

timestamp

------------------------

2013-05-05 08:01:55.75

(1 row)

PostgreSQL also provides functions that return the start time of the current statement, as

well as the actual current time at the instant the function is called. These functions are −

S. No. Function & Description

transaction_timestamp()

It is equivalent to CURRENT_TIMESTAMP, but is named to clearly reflect what

it returns.

statement_timestamp()

It returns the start time of the current statement.

clock_timestamp()

It returns the actual current time, and therefore its value changes even within

a single SQL command.

timeofday()

It returns the actual current time, but as a formatted text string rather than a

timestamp with time zone value.

now()

It is a traditional PostgreSQL equivalent to transaction_timestamp().

DATE_PART(text, timestamp), DATE_PART(text,DATE_PART(text, timestamp), DATE_PART(text,

DATE_PART(text, timestamp), DATE_PART(text,

interval), DATE_TRUNC(text, timestamp)interval), DATE_TRUNC(text, timestamp)

interval), DATE_TRUNC(text, timestamp)

S. No. Function & Description

DATE_PART('field', source)

These functions get the subfields. The field parameter needs to be a string

value, not a name.

The valid field names are: century, day, decade, dow, doy, epoch, hour,

isodow, isoyear, microseconds, millennium, milliseconds, minute, month,

quarter, second, timezone, timezone_hour, timezone_minute, week, year.

DATE_TRUNC('field', source)

This function is conceptually similar to the trunc function for numbers. source

is a value expression of type timestamp or interval. field selects to which

precision to truncate the input value. The return value is of type timestamp or

interval.

The valid values for field are : microseconds, milliseconds, second, minute,

hour, day, week, month, quarter, year, decade, century, millennium

The following are examples for DATE_PART('field', source) functions −

testdb=# SELECT date_part('day', TIMESTAMP '2001-02-16 20:38:40');

date_part

-----------

(1 row)

testdb=# SELECT date_part('hour', INTERVAL '4 hours 3 minutes');

date_part

-----------

(1 row)

The following are examples for DATE_TRUNC('field', source) functions −

testdb=# SELECT date_trunc('hour', TIMESTAMP '2001-02-16 20:38:40');

date_trunc

---------------------

2001-02-16 20:00:00

(1 row)

testdb=# SELECT date_trunc('year', TIMESTAMP '2001-02-16 20:38:40');

date_trunc

---------------------

2001-01-01 00:00:00

(1 row)

The EXTRACT(field FROM source) function retrieves subfields such as year or hour from

date/time values. The source must be a value expression of type timestamp, time, or

interval. The field is an identifier or string that selects what field to extract from the source

value. The EXTRACT function returns values of type double precision.

The following are valid field names (similar to DATE_PART function field names): century,

day, decade, dow, doy, epoch, hour, isodow, isoyear, microseconds, millennium,

milliseconds, minute, month, quarter, second, timezone, timezone_hour, timezone_minute,

week, year.

The following are examples of EXTRACT('field', source) functions −

testdb=# SELECT EXTRACT(CENTURY FROM TIMESTAMP '2000-12-16 12:21:13');

date_part

-----------

(1 row)

testdb=# SELECT EXTRACT(DAY FROM TIMESTAMP '2001-02-16 20:38:40');

date_part

-----------

(1 row)

S. No. Function & Description

ISFINITE(date)

Tests for finite date.

ISFINITE(timestamp)

Tests for finite time stamp.

ISFINITE(interval)

Tests for finite interval.

The following are the examples of the ISFINITE() functions −

EXTRACT(field from timestamp), EXTRACT(field fromEXTRACT(field from timestamp), EXTRACT(field from

EXTRACT(field from timestamp), EXTRACT(field from

interval)interval)

interval)

ISFINITE(date), ISFINITE(timestamp),ISFINITE(date), ISFINITE(timestamp),

ISFINITE(date), ISFINITE(timestamp),

ISFINITE(interval)ISFINITE(interval)

ISFINITE(interval)

testdb=# SELECT isfinite(date '2001-02-16');

isfinite

----------

(1 row)

testdb=# SELECT isfinite(timestamp '2001-02-16 21:28:30');

isfinite

----------

(1 row)

testdb=# SELECT isfinite(interval '4 hours');

isfinite

----------

(1 row)

S. No. Function & Description

JUSTIFY_DAYS(interval)

Adjusts interval so 30-day time periods are represented as months. Return the

interval type

JUSTIFY_HOURS(interval)

Adjusts interval so 24-hour time periods are represented as days. Return the

interval type

JUSTIFY_INTERVAL(interval)

Adjusts interval using JUSTIFY_DAYS and JUSTIFY_HOURS, with additional

sign adjustments. Return the interval type

The following are the examples for the ISFINITE() functions −

testdb=# SELECT justify_days(interval '35 days');

justify_days

--------------

1 mon 5 days

(1 row)

testdb=# SELECT justify_hours(interval '27 hours');

JUSTIFY_DAYS(interval), JUSTIFY_HOURS(interval),JUSTIFY_DAYS(interval), JUSTIFY_HOURS(interval),

JUSTIFY_DAYS(interval), JUSTIFY_HOURS(interval),

JUSTIFY_INTERVAL(interval)JUSTIFY_INTERVAL(interval)

JUSTIFY_INTERVAL(interval)

justify_hours

----------------

1 day 03:00:00

(1 row)

testdb=# SELECT justify_interval(interval '1 mon -1 hour');

justify_interval

------------------

29 days 23:00:00

(1 row)

PostgreSQL - FunctionsPostgreSQL - Functions

PostgreSQL - Functions

PostgreSQL functions, also known as Stored Procedures, allow you to carry out operations

that would normally take several queries and round trips in a single function within the

database. Functions allow database reuse as other applications can interact directly with

your stored procedures instead of a middle-tier or duplicating code.

Functions can be created in a language of your choice like SQL, PL/pgSQL, C, Python, etc.

The basic syntax to create a function is as follows −

CREATE [OR REPLACE] FUNCTION function_name (arguments)

RETURNS return_datatype AS $variable_name$

DECLARE

declaration;

[...]

BEGIN

< function_body >

[...]

RETURN { variable_name | value }

END; LANGUAGE plpgsql;

Where,

function-name specifies the name of the function.

[OR REPLACE] option allows modifying an existing function.

The function must contain a return statement.

RETURN clause specifies that data type you are going to return from the function.

The return_datatype can be a base, composite, or domain type, or can reference

the type of a table column.

function-body contains the executable part.

The AS keyword is used for creating a standalone function.

SyntaxSyntax

Syntax

plpgsql is the name of the language that the function is implemented in. Here, we

use this option for PostgreSQL, it Can be SQL, C, internal, or the name of a user-

defined procedural language. For backward compatibility, the name can be

enclosed by single quotes.

The following example illustrates creating and calling a standalone function. This function

returns the total number of records in the COMPANY table. We will use the COMPANY

table, which has the following records −

testdb# select * from COMPANY;

id | name | age | address | salary

----+-------+-----+-----------+--------

1 | Paul | 32 | California| 20000

2 | Allen | 25 | Texas | 15000

3 | Teddy | 23 | Norway | 20000

4 | Mark | 25 | Rich-Mond | 65000

5 | David | 27 | Texas | 85000

6 | Kim | 22 | South-Hall| 45000

7 | James | 24 | Houston | 10000

(7 rows)

Function totalRecords() is as follows −

CREATE OR REPLACE FUNCTION totalRecords ()

RETURNS integer AS $total$

declare

total integer;

BEGIN

SELECT count(*) into total FROM COMPANY;

RETURN total;

END;

$total$ LANGUAGE plpgsql;

When the above query is executed, the result would be −

testdb# CREATE FUNCTION

Now, let us execute a call to this function and check the records in the COMPANY table

testdb=# select totalRecords();

When the above query is executed, the result would be −

totalrecords

--------------

(1 row)

PostgreSQL - Useful FunctionsPostgreSQL - Useful Functions

PostgreSQL - Useful Functions

ExampleExample

Example

PostgreSQL built-in functions, also called as Aggregate functions, are used for performing
processing on string or numeric data.
The following is the list of all general-purpose PostgreSQL built-in functions −
PostgreSQL  COUNT  Function   −  The  PostgreSQL  COUNT  aggregate  function  is
used to count the number of rows in a database table.
PostgreSQL MAX Function  − The PostgreSQL MAX aggregate function allows us
to select the highest (maximum) value for a certain column.
PostgreSQL  MIN  Function   −  The  PostgreSQL MIN  aggregate  function  allows us
to select the lowest (minimum) value for a certain column.
PostgreSQL AVG Function  − The PostgreSQL AVG aggregate function selects the
average value for certain table column.
PostgreSQL  SUM  Function   −  The  PostgreSQL  SUM  aggregate  function  allows
selecting the total for a numeric column.
PostgreSQL ARRAY Functions  − The PostgreSQL ARRAY aggregate function puts
input values, including nulls, concatenated into an array.
PostgreSQL Numeric Functions  − Complete list of PostgreSQL functions required
to manipulate numbers in SQL.
PostgreSQL String Functions  − Complete list of PostgreSQL functions required to
manipulate strings in PostgreSQL.
PostgreSQL - C/C++ InterfacePostgreSQL - C/C++ Interface
PostgreSQL - C/C++ Interface
This  tutorial  is  going  to  use  libpqxx  library, which  is  the  official  C++  client  API  for
PostgreSQL. The source code for libpqxx is available under the BSD license, so you are free
to  download  it,  pass  it  on  to  others,  change  it,  sell  it,  include  it  in  your  own  code,  and
share your changes with anyone you choose.
The  the  latest  version  of  libpqxx  is  available  to  be  downloaded  from  the  link  Download
Libpqxx . So download the latest version and follow the following steps −
wget http://pqxx.org/download/software/libpqxx/libpqxx-4.0.tar.gz 
tar xvfz libpqxx-4.0.tar.gz 
cd libpqxx-4.0 
./configure 
make 
make install
InstallationInstallation
Installation

Before you start using C/C++ PostgreSQL interface, find the pg_hba.conf file in your

PostgreSQL installation directory and add the following line −

# IPv4 local connections:

host all all 127.0.0.1/32 md5

You can start/restart postgres server in case it is not running using the following command

−

[root@host]# service postgresql restart

Stopping postgresql service: [ OK ]

Starting postgresql service: [ OK ]

The following are important interface routines which can sufice your requirement to work

with PostgreSQL database from your C/C++ program. If you are looking for a more

sophisticated application then you can look into the libpqxx official documentation, or you

can use commercially available APIs.

S. No. API & Description

pqxx::connection C( const std::string & dbstring )

This is a typedef which will be used to connect to the database. Here, dbstring

provides required parameters to connect to the datbase, for example dbname

= testdb user = postgres password=pass123 hostaddr=127.0.0.1

port=5432.

If connection is setup successfully then it creates C with connection object

which provides various useful function public function.

C.is_open()

The method is_open() is a public method of connection object and returns

boolean value. If connection is active, then this method returns true otherwise

it returns false.

C.disconnect()

This method is used to disconnect an opened database connection.

4pqxx::work W( C )

This is a typedef which will be used to create a transactional object using

connection C, which ultimately will be used to execute SQL statements in

C/C++ Interface APIsC/C++ Interface APIs

C/C++ Interface APIs

transactional mode.

If transaction object gets created successfully, then it is assigned to variable W

which will be used to access public methods related to transactional object.

W.exec(const std::string & sql)

This public method from transactional object will be used to execute SQL

statement.

W.commit()

This public method from transactional object will be used to commit the

transaction.

W.abort()

This public method from transactional object will be used to rollback the

transaction.

pqxx::nontransaction N( C )

This is a typedef which will be used to create a non-transactional object using

connection C, which ultimately will be used to execute SQL statements in non-

transactional mode.

If transaction object gets created successfully, then it is assigned to variable N

which will be used to access public methods related to non-transactional

object.

N.exec(const std::string & sql)

This public method from non-transactional object will be used to execute SQL

statement and returns a result object which is actually an interator holding all

the returned records.

The following C code segment shows how to connect to an existing database running on

local machine at port 5432. Here, I used backslash \ for line continuation.

#include <iostream>

#include <pqxx/pqxx>

using namespace std;

Connecting To DatabaseConnecting To Database

Connecting To Database

using namespace pqxx;

int main(int argc, char* argv[]) {

try {

connection C("dbname = testdb user = postgres password = cohondob \

hostaddr = 127.0.0.1 port = 5432");

if (C.is_open()) {

cout << "Opened database successfully: " << C.dbname() << endl;

} else {

cout << "Can't open database" << endl;

return 1;

}

C.disconnect ();

} catch (const std::exception &e) {

cerr << e.what() << std::endl;

return 1;

}

Now, let us compile and run the above program to connect to our database testdb, which

is already available in your schema and can be accessed using user postgres and password

pass123.

You can use the user ID and password based on your database setting. Remember to keep

the -lpqxx and -lpq in the given order! Otherwise, the linker will complain bitterly about

the missing functions with names starting with "PQ."

$g++ test.cpp -lpqxx -lpq

$./a.out

Opened database successfully: testdb

The following C code segment will be used to create a table in previously created database

−

#include <iostream>

#include <pqxx/pqxx>

using namespace std;

using namespace pqxx;

int main(int argc, char* argv[]) {

char * sql;

try {

connection C("dbname = testdb user = postgres password = cohondob \

hostaddr = 127.0.0.1 port = 5432");

if (C.is_open()) {

cout << "Opened database successfully: " << C.dbname() << endl;

} else {

cout << "Can't open database" << endl;

return 1;

}

Create a TableCreate a Table

Create a Table

/* Create SQL statement */

sql = "CREATE TABLE COMPANY(" \

"ID INT PRIMARY KEY NOT NULL," \

"NAME TEXT NOT NULL," \

"AGE INT NOT NULL," \

"ADDRESS CHAR(50)," \

"SALARY REAL );";

/* Create a transactional object. */

work W(C);

/* Execute SQL query */

W.exec( sql );

W.commit();

cout << "Table created successfully" << endl;

C.disconnect ();

} catch (const std::exception &e) {

cerr << e.what() << std::endl;

return 1;

}

return 0;

}

When the above given program is compiled and executed, it will create COMPANY table in

your testdb database and will display the following statements −

Opened database successfully: testdb

Table created successfully

The following C code segment shows how we can create records in our COMPANY table

created in above example −

#include <iostream>

#include <pqxx/pqxx>

using namespace std;

using namespace pqxx;

int main(int argc, char* argv[]) {

char * sql;

try {

connection C("dbname = testdb user = postgres password = cohondob \

hostaddr = 127.0.0.1 port = 5432");

if (C.is_open()) {

cout << "Opened database successfully: " << C.dbname() << endl;

} else {

cout << "Can't open database" << endl;

return 1;

}

/* Create SQL statement */

sql = "INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) " \

"VALUES (1, 'Paul', 32, 'California', 20000.00 ); " \

INSERT OperationINSERT Operation

INSERT Operation

"INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) " \

"VALUES (2, 'Allen', 25, 'Texas', 15000.00 ); " \

"INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)" \

"VALUES (3, 'Teddy', 23, 'Norway', 20000.00 );" \

"INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)" \

"VALUES (4, 'Mark', 25, 'Rich-Mond ', 65000.00 );";

/* Create a transactional object. */

work W(C);

/* Execute SQL query */

W.exec( sql );

W.commit();

cout << "Records created successfully" << endl;

C.disconnect ();

} catch (const std::exception &e) {

cerr << e.what() << std::endl;

return 1;

}

return 0;

}

When the above given program is compiled and executed, it will create given records in

COMPANY table and will display the following two lines −

Opened database successfully: testdb

Records created successfully

The following C code segment shows how we can fetch and display records from our

COMPANY table created in above example −

#include <iostream>

#include <pqxx/pqxx>

using namespace std;

using namespace pqxx;

int main(int argc, char* argv[]) {

char * sql;

try {

connection C("dbname = testdb user = postgres password = cohondob \

hostaddr = 127.0.0.1 port = 5432");

if (C.is_open()) {

cout << "Opened database successfully: " << C.dbname() << endl;

} else {

cout << "Can't open database" << endl;

return 1;

}

/* Create SQL statement */

sql = "SELECT * from COMPANY";

/* Create a non-transactional object. */

SELECT OperationSELECT Operation

SELECT Operation

nontransaction N(C);

/* Execute SQL query */

result R( N.exec( sql ));

/* List down all the records */

for (result::const_iterator c = R.begin(); c != R.end(); ++c) {

cout << "ID = " << c[0].as<int>() << endl;

cout << "Name = " << c[1].as<string>() << endl;

cout << "Age = " << c[2].as<int>() << endl;

cout << "Address = " << c[3].as<string>() << endl;

cout << "Salary = " << c[4].as<float>() << endl;

}

cout << "Operation done successfully" << endl;

C.disconnect ();

} catch (const std::exception &e) {

cerr << e.what() << std::endl;

return 1;

}

return 0;

}

When the above given program is compiled and executed, it will produce the following

result −

Opened database successfully: testdb

ID = 1

Name = Paul

Age = 32

Address = California

Salary = 20000

ID = 2

Name = Allen

Age = 25

Address = Texas

Salary = 15000

ID = 3

Name = Teddy

Age = 23

Address = Norway

Salary = 20000

ID = 4

Name = Mark

Age = 25

Address = Rich-Mond

Salary = 65000

Operation done successfully

UPDATE OperationUPDATE Operation

UPDATE Operation

The following C code segment shows how we can use the UPDATE statement to update any

record and then fetch and display updated records from our COMPANY table −

#include <iostream>

#include <pqxx/pqxx>

using namespace std;

using namespace pqxx;

int main(int argc, char* argv[]) {

char * sql;

try {

connection C("dbname = testdb user = postgres password = cohondob \

hostaddr = 127.0.0.1 port = 5432");

if (C.is_open()) {

cout << "Opened database successfully: " << C.dbname() << endl;

} else {

cout << "Can't open database" << endl;

return 1;

}

/* Create a transactional object. */

work W(C);

/* Create SQL UPDATE statement */

sql = "UPDATE COMPANY set SALARY = 25000.00 where ID=1";

/* Execute SQL query */

W.exec( sql );

W.commit();

cout << "Records updated successfully" << endl;

/* Create SQL SELECT statement */

sql = "SELECT * from COMPANY";

/* Create a non-transactional object. */

nontransaction N(C);

/* Execute SQL query */

result R( N.exec( sql ));

/* List down all the records */

for (result::const_iterator c = R.begin(); c != R.end(); ++c) {

cout << "ID = " << c[0].as<int>() << endl;

cout << "Name = " << c[1].as<string>() << endl;

cout << "Age = " << c[2].as<int>() << endl;

cout << "Address = " << c[3].as<string>() << endl;

cout << "Salary = " << c[4].as<float>() << endl;

}

cout << "Operation done successfully" << endl;

C.disconnect ();

} catch (const std::exception &e) {

cerr << e.what() << std::endl;

return 1;

}

return 0;

}

When the above given program is compiled and executed, it will produce the following

result −

Opened database successfully: testdb

Records updated successfully

ID = 2

Name = Allen

Age = 25

Address = Texas

Salary = 15000

ID = 3

Name = Teddy

Age = 23

Address = Norway

Salary = 20000

ID = 4

Name = Mark

Age = 25

Address = Rich-Mond

Salary = 65000

ID = 1

Name = Paul

Age = 32

Address = California

Salary = 25000

Operation done successfully

The following C code segment shows how we can use the DELETE statement to delete any

record and then fetch and display remaining records from our COMPANY table −

#include <iostream>

#include <pqxx/pqxx>

using namespace std;

using namespace pqxx;

int main(int argc, char* argv[]) {

char * sql;

try {

connection C("dbname = testdb user = postgres password = cohondob \

hostaddr = 127.0.0.1 port = 5432");

if (C.is_open()) {

cout << "Opened database successfully: " << C.dbname() << endl;

} else {

cout << "Can't open database" << endl;

return 1;

DELETE OperationDELETE Operation

DELETE Operation

}

/* Create a transactional object. */

work W(C);

/* Create SQL DELETE statement */

sql = "DELETE from COMPANY where ID = 2";

/* Execute SQL query */

W.exec( sql );

W.commit();

cout << "Records deleted successfully" << endl;

/* Create SQL SELECT statement */

sql = "SELECT * from COMPANY";

/* Create a non-transactional object. */

nontransaction N(C);

/* Execute SQL query */

result R( N.exec( sql ));

/* List down all the records */

for (result::const_iterator c = R.begin(); c != R.end(); ++c) {

cout << "ID = " << c[0].as<int>() << endl;

cout << "Name = " << c[1].as<string>() << endl;

cout << "Age = " << c[2].as<int>() << endl;

cout << "Address = " << c[3].as<string>() << endl;

cout << "Salary = " << c[4].as<float>() << endl;

}

cout << "Operation done successfully" << endl;

C.disconnect ();

} catch (const std::exception &e) {

cerr << e.what() << std::endl;

return 1;

}

return 0;

}

When the above given program is compiled and executed, it will produce the following

result −

Opened database successfully: testdb

Records deleted successfully

ID = 3

Name = Teddy

Age = 23

Address = Norway

Salary = 20000

ID = 4

Name = Mark

Age = 25

Address = Rich-Mond

Salary = 65000

ID = 1

Name = Paul

Age = 32

Address = California

Salary = 25000

Operation done successfully

PostgreSQL - JAVA InterfacePostgreSQL - JAVA Interface

PostgreSQL - JAVA Interface

Before we start using PostgreSQL in our Java programs, we need to make sure that we

have PostgreSQL JDBC and Java set up on the machine. You can check Java tutorial for

Java installation on your machine. Now let us check how to set up PostgreSQL JDBC driver.

Download the latest version of postgresql-(VERSION).jdbc.jar from postgresql-

jdbc repository.

Add downloaded jar file postgresql-(VERSION).jdbc.jar in your class path, or you

can use it along with -classpath option as explained below in the examples.

The following section assumes you have little knowledge about Java JDBC concepts. If you

do not have, then it is suggested to spent half and hour with JDBC Tutorial to become

comfortable with concepts explained below.

The following Java code shows how to connect to an existing database. If the database

does not exist, then it will be created and finally a database object will be returned.

import java.sql.Connection;

import java.sql.DriverManager;

public class PostgreSQLJDBC {

public static void main(String args[]) {

Connection c = null;

try {

Class.forName("org.postgresql.Driver");

c = DriverManager

.getConnection("jdbc:postgresql://localhost:5432/testdb",

"postgres", "123");

} catch (Exception e) {

e.printStackTrace();

System.err.println(e.getClass().getName()+": "+e.getMessage());

System.exit(0);

}

System.out.println("Opened database successfully");

}

Before you compile and run above program, find pg_hba.conf file in your PostgreSQL

installation directory and add the following line −

InstallationInstallation

Installation

Connecting To DatabaseConnecting To Database

Connecting To Database

# IPv4 local connections:

host all all 127.0.0.1/32 md5

You can start/restart the postgres server in case it is not running using the following

command −

[root@host]# service postgresql restart

Stopping postgresql service: [ OK ]

Starting postgresql service: [ OK ]

Now, let us compile and run the above program to connect with testdb. Here, we are using

postgres as user ID and 123 as password to access the database. You can change this as

per your database configuration and setup. We are also assuming current version of JDBC

driver postgresql-9.2-1002.jdbc3.jar is available in the current path.

The following Java program will be used to create a table in previously opened database.

Make sure you do not have this table already in your target database.

import java.sql.*;

import java.sql.Connection;

import java.sql.DriverManager;

import java.sql.Statement;

public class PostgreSQLJDBC {

public static void main( String args[] ) {

Connection c = null;

Statement stmt = null;

try {

Class.forName("org.postgresql.Driver");

c = DriverManager

.getConnection("jdbc:postgresql://localhost:5432/testdb",

"manisha", "123");

System.out.println("Opened database successfully");

stmt = c.createStatement();

String sql = "CREATE TABLE COMPANY " +

"(ID INT PRIMARY KEY NOT NULL," +

" NAME TEXT NOT NULL, " +

" AGE INT NOT NULL, " +

" ADDRESS CHAR(50), " +

" SALARY REAL)";

stmt.executeUpdate(sql);

stmt.close();

c.close();

} catch ( Exception e ) {

C:\JavaPostgresIntegration>javac PostgreSQLJDBC.java

C:\JavaPostgresIntegration>java -cp c:\tools\postgresql-9.2-1002.jdbc3.jar;C:\JavaPostgresIntegra

Open database successfully

Create a TableCreate a Table

Create a Table

System.err.println( e.getClass().getName()+": "+ e.getMessage() );

System.exit(0);

}

System.out.println("Table created successfully");

}

When a program is compiled and executed, it will create the COMPANY table in testdb

database and will display the following two lines −

Opened database successfully

Table created successfully

The following Java program shows how we can create records in our COMPANY table

created in above example −

import java.sql.Connection;

import java.sql.DriverManager;

import java.sql.Statement;

public class PostgreSQLJDBC {

public static void main(String args[]) {

Connection c = null;

Statement stmt = null;

try {

Class.forName("org.postgresql.Driver");

c = DriverManager

.getConnection("jdbc:postgresql://localhost:5432/testdb",

"manisha", "123");

c.setAutoCommit(false);

System.out.println("Opened database successfully");

stmt = c.createStatement();

String sql = "INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) "

+ "VALUES (1, 'Paul', 32, 'California', 20000.00 );";

stmt.executeUpdate(sql);

sql = "INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) "

+ "VALUES (2, 'Allen', 25, 'Texas', 15000.00 );";

stmt.executeUpdate(sql);

sql = "INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) "

+ "VALUES (3, 'Teddy', 23, 'Norway', 20000.00 );";

stmt.executeUpdate(sql);

sql = "INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) "

+ "VALUES (4, 'Mark', 25, 'Rich-Mond ', 65000.00 );";

stmt.executeUpdate(sql);

stmt.close();

c.commit();

c.close();

} catch (Exception e) {

System.err.println( e.getClass().getName()+": "+ e.getMessage() );

System.exit(0);

INSERT OperationINSERT Operation

INSERT Operation

}

System.out.println("Records created successfully");

}

When the above program is compiled and executed, it will create given records in

COMPANY table and will display the following two lines −

Opened database successfully

Records created successfully

The following Java program shows how we can fetch and display records from our

COMPANY table created in above example −

import java.sql.Connection;

import java.sql.DriverManager;

import java.sql.ResultSet;

import java.sql.Statement;

public class PostgreSQLJDBC {

public static void main( String args[] ) {

Connection c = null;

Statement stmt = null;

try {

Class.forName("org.postgresql.Driver");

c = DriverManager

.getConnection("jdbc:postgresql://localhost:5432/testdb",

"manisha", "123");

c.setAutoCommit(false);

System.out.println("Opened database successfully");

stmt = c.createStatement();

ResultSet rs = stmt.executeQuery( "SELECT * FROM COMPANY;" );

while ( rs.next() ) {

int id = rs.getInt("id");

String name = rs.getString("name");

int age = rs.getInt("age");

String address = rs.getString("address");

float salary = rs.getFloat("salary");

System.out.println( "ID = " + id );

System.out.println( "NAME = " + name );

System.out.println( "AGE = " + age );

System.out.println( "ADDRESS = " + address );

System.out.println( "SALARY = " + salary );

System.out.println();

}

rs.close();

stmt.close();

c.close();

} catch ( Exception e ) {

System.err.println( e.getClass().getName()+": "+ e.getMessage() );

System.exit(0);

}

System.out.println("Operation done successfully");

SELECT OperationSELECT Operation

SELECT Operation

}

When the program is compiled and executed, it will produce the following result −

Opened database successfully

ID = 1

NAME = Paul

AGE = 32

ADDRESS = California

SALARY = 20000.0

ID = 2

NAME = Allen

AGE = 25

ADDRESS = Texas

SALARY = 15000.0

ID = 3

NAME = Teddy

AGE = 23

ADDRESS = Norway

SALARY = 20000.0

ID = 4

NAME = Mark

AGE = 25

ADDRESS = Rich-Mond

SALARY = 65000.0

Operation done successfully

The following Java code shows how we can use the UPDATE statement to update any

record and then fetch and display updated records from our COMPANY table −

import java.sql.Connection;

import java.sql.DriverManager;

import java.sql.ResultSet;

import java.sql.Statement;

public class PostgreSQLJDBC {

public static void main( String args[] ) {

Connection c = null;

Statement stmt = null;

try {

UPDATE OperationUPDATE Operation

UPDATE Operation

Class.forName("org.postgresql.Driver");

c = DriverManager

.getConnection("jdbc:postgresql://localhost:5432/testdb",

"manisha", "123");

c.setAutoCommit(false);

System.out.println("Opened database successfully");

stmt = c.createStatement();

String sql = "UPDATE COMPANY set SALARY = 25000.00 where ID=1;";

stmt.executeUpdate(sql);

c.commit();

ResultSet rs = stmt.executeQuery( "SELECT * FROM COMPANY;" );

while ( rs.next() ) {

int id = rs.getInt("id");

String name = rs.getString("name");

int age = rs.getInt("age");

String address = rs.getString("address");

float salary = rs.getFloat("salary");

System.out.println( "ID = " + id );

System.out.println( "NAME = " + name );

System.out.println( "AGE = " + age );

System.out.println( "ADDRESS = " + address );

System.out.println( "SALARY = " + salary );

System.out.println();

}

rs.close();

stmt.close();

c.close();

} catch ( Exception e ) {

System.err.println( e.getClass().getName()+": "+ e.getMessage() );

System.exit(0);

}

System.out.println("Operation done successfully");

}

When the program is compiled and executed, it will produce the following result −

Opened database successfully

ID = 2

NAME = Allen

AGE = 25

ADDRESS = Texas

SALARY = 15000.0

ID = 3

NAME = Teddy

AGE = 23

ADDRESS = Norway

SALARY = 20000.0

ID = 4

NAME = Mark

AGE = 25

ADDRESS = Rich-Mond

SALARY = 65000.0

ID = 1

NAME = Paul

AGE = 32

ADDRESS = California

SALARY = 25000.0

Operation done successfully

The following Java code shows how we can use the DELETE statement to delete any record

and then fetch and display remaining records from our COMPANY table −

import java.sql.Connection;

import java.sql.DriverManager;

import java.sql.ResultSet;

import java.sql.Statement;

public class PostgreSQLJDBC6 {

public static void main( String args[] ) {

Connection c = null;

Statement stmt = null;

try {

Class.forName("org.postgresql.Driver");

c = DriverManager

.getConnection("jdbc:postgresql://localhost:5432/testdb",

"manisha", "123");

c.setAutoCommit(false);

System.out.println("Opened database successfully");

stmt = c.createStatement();

String sql = "DELETE from COMPANY where ID = 2;";

stmt.executeUpdate(sql);

c.commit();

ResultSet rs = stmt.executeQuery( "SELECT * FROM COMPANY;" );

while ( rs.next() ) {

int id = rs.getInt("id");

String name = rs.getString("name");

int age = rs.getInt("age");

String address = rs.getString("address");

float salary = rs.getFloat("salary");

System.out.println( "ID = " + id );

System.out.println( "NAME = " + name );

System.out.println( "AGE = " + age );

System.out.println( "ADDRESS = " + address );

System.out.println( "SALARY = " + salary );

System.out.println();

}

DELETE OperationDELETE Operation

DELETE Operation

rs.close();

stmt.close();

c.close();

} catch ( Exception e ) {

System.err.println( e.getClass().getName()+": "+ e.getMessage() );

System.exit(0);

}

System.out.println("Operation done successfully");

}

When the program is compiled and executed, it will produce the following result −

Opened database successfully

ID = 3

NAME = Teddy

AGE = 23

ADDRESS = Norway

SALARY = 20000.0

ID = 4

NAME = Mark

AGE = 25

ADDRESS = Rich-Mond

SALARY = 65000.0

ID = 1

NAME = Paul

AGE = 32

ADDRESS = California

SALARY = 25000.0

Operation done successfully

PostgreSQL - PHP InterfacePostgreSQL - PHP Interface

PostgreSQL - PHP Interface

The PostgreSQL extension is enabled by default in the latest releases of PHP 5.3.x. It is

possible to disable it by using --without-pgsql at compile time. Still you can use yum

command to install PHP -PostgreSQL interface −

yum install php-pgsql

Before you start using the PHP PostgreSQL interface, find the pg_hba.conf file in your

PostgreSQL installation directory and add the following line −

# IPv4 local connections:

host all all 127.0.0.1/32 md5

InstallationInstallation

Installation

You can start/restart the postgres server, in case it is not running, using the following

command −

[root@host]# service postgresql restart

Stopping postgresql service: [ OK ]

Starting postgresql service: [ OK ]

Windows users must enable php_pgsql.dll in order to use this extension. This DLL is

included with Windows distributions in the latest releases of PHP 5.3.x

For detailed installation instructions, kindly check our PHP tutorial and its official website.

The following are important PHP routines, which can suffice your requirement to work with

PostgreSQL database from your PHP program. If you are looking for a more sophisticated

application, then you can look into the PHP official documentation.

S. No. API & Description

resource pg_connect ( string $connection_string [, int $connect_type

] )

This opens a connection to a PostgreSQL database specified by the

connection_string.

If PGSQL_CONNECT_FORCE_NEW is passed as connect_type, then a new

connection is created in case of a second call to pg_connect(), even if the

connection_string is identical to an existing connection.

bool pg_connection_reset ( resource $connection )

This routine resets the connection. It is useful for error recovery. Returns

TRUE on success or FALSE on failure.

int pg_connection_status ( resource $connection )

This routine returns the status of the specified connection. Returns

PGSQL_CONNECTION_OK or PGSQL_CONNECTION_BAD.

string pg_dbname ([ resource $connection ] )

This routine returns the name of the database that the given PostgreSQL

connection resource.

5resource pg_prepare ([ resource $connection ], string $stmtname,

PHP Interface APIsPHP Interface APIs

PHP Interface APIs

string $query )

This submits a request to create a prepared statement with the given

parameters and waits for completion.

resource pg_execute ([ resource $connection ], string $stmtname,

array $params )

This routine sends a request to execute a prepared statement with given

parameters and waits for the result.

resource pg_query ([ resource $connection ], string $query )

This routine executes the query on the specified database connection.

array pg_fetch_row ( resource $result [, int $row ] )

This routine fetches one row of data from the result associated with the

specified result resource.

array pg_fetch_all ( resource $result )

This routine returns an array that contains all rows (records) in the result

resource.

int pg_affected_rows ( resource $result )

This routine returns the number of rows affected by INSERT, UPDATE, and

DELETE queries.

int pg_num_rows ( resource $result )

This routine returns the number of rows in a PostgreSQL result resource for

example number of rows returned by SELECT statement.

bool pg_close ([ resource $connection ] )

This routine closes the non-persistent connection to a PostgreSQL database

associated with the given connection resource.

string pg_last_error ([ resource $connection ] )

This routine returns the last error message for a given connection.

14 string pg_escape_literal ([ resource $connection ], string $data )

This routine escapes a literal for insertion into a text field.

string pg_escape_string ([ resource $connection ], string $data )

This routine escapes a string for querying the database.

The following PHP code shows how to connect to an existing database on a local machine

and finally a database connection object will be returned.

<?php

$host = "host = 127.0.0.1";

$port = "port = 5432";

$dbname = "dbname = testdb";

$credentials = "user = postgres password=pass123";

$db = pg_connect( "$host $port $dbname $credentials" );

if(!$db) {

echo "Error : Unable to open database\n";

} else {

echo "Opened database successfully\n";

}

Now, let us run the above given program to open our database testdb: if the database is

successfully opened, then it will give the following message −

Opened database successfully

The following PHP program will be used to create a table in a previously created database

−

<?php

$host = "host = 127.0.0.1";

$port = "port = 5432";

$dbname = "dbname = testdb";

$credentials = "user = postgres password=pass123";

$db = pg_connect( "$host $port $dbname $credentials" );

if(!$db) {

echo "Error : Unable to open database\n";

} else {

echo "Opened database successfully\n";

}

$sql =<<<EOF

CREATE TABLE COMPANY

(ID INT PRIMARY KEY NOT NULL,

NAME TEXT NOT NULL,

Connecting to DatabaseConnecting to Database

Connecting to Database

Create a TableCreate a Table

Create a Table

AGE INT NOT NULL,

ADDRESS CHAR(50),

SALARY REAL);

EOF;

$ret = pg_query($db, $sql);

if(!$ret) {

echo pg_last_error($db);

} else {

echo "Table created successfully\n";

}

pg_close($db);

When the above given program is executed, it will create COMPANY table in your testdb

and it will display the following messages −

Opened database successfully

Table created successfully

The following PHP program shows how we can create records in our COMPANY table

created in above example −

<?php

$host = "host=127.0.0.1";

$port = "port=5432";

$dbname = "dbname = testdb";

$credentials = "user = postgres password=pass123";

$db = pg_connect( "$host $port $dbname $credentials" );

if(!$db) {

echo "Error : Unable to open database\n";

} else {

echo "Opened database successfully\n";

}

$sql =<<<EOF

INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)

VALUES (1, 'Paul', 32, 'California', 20000.00 );

INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)

VALUES (2, 'Allen', 25, 'Texas', 15000.00 );

INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)

VALUES (3, 'Teddy', 23, 'Norway', 20000.00 );

INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)

VALUES (4, 'Mark', 25, 'Rich-Mond ', 65000.00 );

EOF;

$ret = pg_query($db, $sql);

if(!$ret) {

echo pg_last_error($db);

} else {

echo "Records created successfully\n";

INSERT OperationINSERT Operation

INSERT Operation

}

pg_close($db);

When the above given program is executed, it will create the given records in COMPANY

table and will display the following two lines −

Opened database successfully

Records created successfully

The following PHP program shows how we can fetch and display records from our

COMPANY table created in above example −

<?php

$host = "host = 127.0.0.1";

$port = "port = 5432";

$dbname = "dbname = testdb";

$credentials = "user = postgres password=pass123";

$db = pg_connect( "$host $port $dbname $credentials" );

if(!$db) {

echo "Error : Unable to open database\n";

} else {

echo "Opened database successfully\n";

}

$sql =<<<EOF

SELECT * from COMPANY;

EOF;

$ret = pg_query($db, $sql);

if(!$ret) {

echo pg_last_error($db);

exit;

}

while($row = pg_fetch_row($ret)) {

echo "ID = ". $row[0] . "\n";

echo "NAME = ". $row[1] ."\n";

echo "ADDRESS = ". $row[2] ."\n";

echo "SALARY = ".$row[4] ."\n\n";

}

echo "Operation done successfully\n";

pg_close($db);

When the above given program is executed, it will produce the following result. Keep a

note that fields are returned in the sequence they were used while creating table.

Opened database successfully

ID = 1

NAME = Paul

ADDRESS = California

SELECT OperationSELECT Operation

SELECT Operation

SALARY = 20000

ID = 2

NAME = Allen

ADDRESS = Texas

SALARY = 15000

ID = 3

NAME = Teddy

ADDRESS = Norway

SALARY = 20000

ID = 4

NAME = Mark

ADDRESS = Rich-Mond

SALARY = 65000

Operation done successfully

The following PHP code shows how we can use the UPDATE statement to update any

record and then fetch and display updated records from our COMPANY table −

<?php

$host = "host=127.0.0.1";

$port = "port=5432";

$dbname = "dbname = testdb";

$credentials = "user = postgres password=pass123";

$db = pg_connect( "$host $port $dbname $credentials" );

if(!$db) {

echo "Error : Unable to open database\n";

} else {

echo "Opened database successfully\n";

}

$sql =<<<EOF

UPDATE COMPANY set SALARY = 25000.00 where ID=1;

EOF;

$ret = pg_query($db, $sql);

if(!$ret) {

echo pg_last_error($db);

exit;

} else {

echo "Record updated successfully\n";

}

$sql =<<<EOF

SELECT * from COMPANY;

EOF;

$ret = pg_query($db, $sql);

UPDATE OperationUPDATE Operation

UPDATE Operation

if(!$ret) {

echo pg_last_error($db);

exit;

}

while($row = pg_fetch_row($ret)) {

echo "ID = ". $row[0] . "\n";

echo "NAME = ". $row[1] ."\n";

echo "ADDRESS = ". $row[2] ."\n";

echo "SALARY = ".$row[4] ."\n\n";

}

echo "Operation done successfully\n";

pg_close($db);

When the above given program is executed, it will produce the following result −

Opened database successfully

Record updated successfully

ID = 2

NAME = Allen

ADDRESS = 25

SALARY = 15000

ID = 3

NAME = Teddy

ADDRESS = 23

SALARY = 20000

ID = 4

NAME = Mark

ADDRESS = 25

SALARY = 65000

ID = 1

NAME = Paul

ADDRESS = 32

SALARY = 25000

Operation done successfully

The following PHP code shows how we can use the DELETE statement to delete any record

and then fetch and display the remaining records from our COMPANY table −

<?php

$host = "host = 127.0.0.1";

$port = "port = 5432";

$dbname = "dbname = testdb";

DELETE OperationDELETE Operation

DELETE Operation

$credentials = "user = postgres password=pass123";

$db = pg_connect( "$host $port $dbname $credentials" );

if(!$db) {

echo "Error : Unable to open database\n";

} else {

echo "Opened database successfully\n";

}

$sql =<<<EOF

DELETE from COMPANY where ID=2;

EOF;

$ret = pg_query($db, $sql);

if(!$ret) {

echo pg_last_error($db);

exit;

} else {

echo "Record deleted successfully\n";

}

$sql =<<<EOF

SELECT * from COMPANY;

EOF;

$ret = pg_query($db, $sql);

if(!$ret) {

echo pg_last_error($db);

exit;

}

while($row = pg_fetch_row($ret)) {

echo "ID = ". $row[0] . "\n";

echo "NAME = ". $row[1] ."\n";

echo "ADDRESS = ". $row[2] ."\n";

echo "SALARY = ".$row[4] ."\n\n";

}

echo "Operation done successfully\n";

pg_close($db);

When the above given program is executed, it will produce the following result −

Opened database successfully

Record deleted successfully

ID = 3

NAME = Teddy

ADDRESS = 23

SALARY = 20000

ID = 4

NAME = Mark

ADDRESS = 25

SALARY = 65000

ID = 1

NAME = Paul

ADDRESS = 32

SALARY = 25000

Operation done successfully

PostgreSQL - Perl InterfacePostgreSQL - Perl Interface

PostgreSQL - Perl Interface

The PostgreSQL can be integrated with Perl using Perl DBI module, which is a database

access module for the Perl programming language. It defines a set of methods, variables

and conventions that provide a standard database interface.

Here are simple steps to install DBI module on your Linux/Unix machine −

$ wget http://search.cpan.org/CPAN/authors/id/T/TI/TIMB/DBI-1.625.tar.gz

$ tar xvfz DBI-1.625.tar.gz

$ cd DBI-1.625

$ perl Makefile.PL

$ make

$ make install

If you need to install SQLite driver for DBI, then it can be installed as follows −

$ wget http://search.cpan.org/CPAN/authors/id/T/TU/TURNSTEP/DBD-Pg-2.19.3.tar.gz

$ tar xvfz DBD-Pg-2.19.3.tar.gz

$ cd DBD-Pg-2.19.3

$ perl Makefile.PL

$ make

$ make install

Before you start using Perl PostgreSQL interface, find the pg_hba.conf file in your

PostgreSQL installation directory and add the following line −

# IPv4 local connections:

host all all 127.0.0.1/32 md5

You can start/restart the postgres server, in case it is not running, using the following

command −

[root@host]# service postgresql restart

Stopping postgresql service: [ OK ]

Starting postgresql service: [ OK ]

Following are the important DBI routines, which can suffice your requirement to work with

SQLite database from your Perl program. If you are looking for a more sophisticated

application, then you can look into Perl DBI official documentation.

InstallationInstallation

Installation

DBI Interface APIsDBI Interface APIs

DBI Interface APIs

S. No. API & Description

DBI→connect($data_source, "userid", "password", \%attr)

Establishes a database connection, or session, to the requested $data_source.

Returns a database handle object if the connection succeeds.

Datasource has the form like :

DBI:Pg:dbname=$database;host=127.0.0.1;port=5432 Pg is

PostgreSQL driver name and testdb is the name of database.

$dbh→do($sql)

This routine prepares and executes a single SQL statement. Returns the

number of rows affected or undef on error. A return value of -1 means the

number of rows is not known, not applicable, or not available. Here $dbh is a

handle returned by DBI→connect() call.

$dbh→prepare($sql)

This routine prepares a statement for later execution by the database engine

and returns a reference to a statement handle object.

$sth→execute()

This routine performs whatever processing is necessary to execute the

prepared statement. An undef is returned if an error occurs. A successful

execute always returns true regardless of the number of rows affected. Here

$sth is a statement handle returned by $dbh→prepare($sql) call.

$sth→fetchrow_array()

This routine fetches the next row of data and returns it as a list containing the

field values. Null fields are returned as undef values in the list.

$DBI::err

This is equivalent to $h→err, where $h is any of the handle types like $dbh,

$sth, or $drh. This returns native database engine error code from the last

driver method called.

7$DBI::errstr

This is equivalent to $h→errstr, where $h is any of the handle types like $dbh,

$sth, or $drh. This returns the native database engine error message from the

last DBI method called.

$dbh->disconnect()

This routine closes a database connection previously opened by a call to

DBI→connect().

The following Perl code shows how to connect to an existing database. If the database

does not exist, then it will be created and finally a database object will be returned.

#!/usr/bin/perl

use DBI;

use strict;

my $driver = "Pg";

my $database = "testdb";

my $dsn = "DBI:$driver:dbname = $database;host = 127.0.0.1;port = 5432";

my $userid = "postgres";

my $password = "pass123";

my $dbh = DBI->connect($dsn, $userid, $password, { RaiseError => 1 })

or die $DBI::errstr;

print "Opened database successfully\n";

Now, let us run the above given program to open our database testdb; if the database is

successfully opened then it will give the following message −

Open database successfully

The following Perl program will be used to create a table in previously created database −

#!/usr/bin/perl

use DBI;

use strict;

my $driver = "Pg";

my $database = "testdb";

my $dsn = "DBI:$driver:dbname=$database;host=127.0.0.1;port=5432";

my $userid = "postgres";

my $password = "pass123";

my $dbh = DBI->connect($dsn, $userid, $password, { RaiseError => 1 })

or die $DBI::errstr;

print "Opened database successfully\n";

my $stmt = qq(CREATE TABLE COMPANY

(ID INT PRIMARY KEY NOT NULL,

Connecting to DatabaseConnecting to Database

Connecting to Database

Create a TableCreate a Table

Create a Table

NAME TEXT NOT NULL,

AGE INT NOT NULL,

ADDRESS CHAR(50),

SALARY REAL););

my $rv = $dbh->do($stmt);

if($rv < 0) {

print $DBI::errstr;

} else {

print "Table created successfully\n";

}

$dbh->disconnect();

When the above given program is executed, it will create COMPANY table in your testdb

and it will display the following messages −

Opened database successfully

Table created successfully

The following Perl program shows how we can create records in our COMPANY table

created in above example −

#!/usr/bin/perl

use DBI;

use strict;

my $driver = "Pg";

my $database = "testdb";

my $dsn = "DBI:$driver:dbname = $database;host = 127.0.0.1;port = 5432";

my $userid = "postgres";

my $password = "pass123";

my $dbh = DBI->connect($dsn, $userid, $password, { RaiseError => 1 })

or die $DBI::errstr;

print "Opened database successfully\n";

my $stmt = qq(INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)

VALUES (1, 'Paul', 32, 'California', 20000.00 ));

my $rv = $dbh->do($stmt) or die $DBI::errstr;

$stmt = qq(INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)

VALUES (2, 'Allen', 25, 'Texas', 15000.00 ));

$rv = $dbh->do($stmt) or die $DBI::errstr;

$stmt = qq(INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)

VALUES (3, 'Teddy', 23, 'Norway', 20000.00 ));

$rv = $dbh->do($stmt) or die $DBI::errstr;

$stmt = qq(INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY)

VALUES (4, 'Mark', 25, 'Rich-Mond ', 65000.00 ););

$rv = $dbh->do($stmt) or die $DBI::errstr;

print "Records created successfully\n";

$dbh->disconnect();

INSERT OperationINSERT Operation

INSERT Operation

When the above given program is executed, it will create given records in COMPANY table

and will display the following two lines −

Opened database successfully

Records created successfully

The following Perl program shows how we can fetch and display records from our

COMPANY table created in above example −

#!/usr/bin/perl

use DBI;

use strict;

my $driver = "Pg";

my $database = "testdb";

my $dsn = "DBI:$driver:dbname = $database;host = 127.0.0.1;port = 5432";

my $userid = "postgres";

my $password = "pass123";

my $dbh = DBI->connect($dsn, $userid, $password, { RaiseError => 1 })

or die $DBI::errstr;

print "Opened database successfully\n";

my $stmt = qq(SELECT id, name, address, salary from COMPANY;);

my $sth = $dbh->prepare( $stmt );

my $rv = $sth->execute() or die $DBI::errstr;

if($rv < 0) {

print $DBI::errstr;

}

while(my @row = $sth->fetchrow_array()) {

print "ID = ". $row[0] . "\n";

print "NAME = ". $row[1] ."\n";

print "ADDRESS = ". $row[2] ."\n";

print "SALARY = ". $row[3] ."\n\n";

}

print "Operation done successfully\n";

$dbh->disconnect();

When the above given program is executed, it will produce the following result −

Opened database successfully

ID = 1

NAME = Paul

ADDRESS = California

SALARY = 20000

ID = 2

NAME = Allen

ADDRESS = Texas

SALARY = 15000

SELECT OperationSELECT Operation

SELECT Operation

ID = 3

NAME = Teddy

ADDRESS = Norway

SALARY = 20000

ID = 4

NAME = Mark

ADDRESS = Rich-Mond

SALARY = 65000

Operation done successfully

The following Perl code shows how we can use the UPDATE statement to update any record

and then fetch and display updated records from our COMPANY table −

#!/usr/bin/perl

use DBI;

use strict;

my $driver = "Pg";

my $database = "testdb";

my $dsn = "DBI:$driver:dbname = $database;host = 127.0.0.1;port = 5432";

my $userid = "postgres";

my $password = "pass123";

my $dbh = DBI->connect($dsn, $userid, $password, { RaiseError => 1 })

or die $DBI::errstr;

print "Opened database successfully\n";

my $stmt = qq(UPDATE COMPANY set SALARY = 25000.00 where ID=1;);

my $rv = $dbh->do($stmt) or die $DBI::errstr;

if( $rv < 0 ) {

print $DBI::errstr;

}else{

print "Total number of rows updated : $rv\n";

}

$stmt = qq(SELECT id, name, address, salary from COMPANY;);

my $sth = $dbh->prepare( $stmt );

$rv = $sth->execute() or die $DBI::errstr;

if($rv < 0) {

print $DBI::errstr;

}

while(my @row = $sth->fetchrow_array()) {

print "ID = ". $row[0] . "\n";

print "NAME = ". $row[1] ."\n";

print "ADDRESS = ". $row[2] ."\n";

print "SALARY = ". $row[3] ."\n\n";

}

print "Operation done successfully\n";

$dbh->disconnect();

UPDATE OperationUPDATE Operation

UPDATE Operation

When the above given program is executed, it will produce the following result −

Opened database successfully

Total number of rows updated : 1

ID = 1

NAME = Paul

ADDRESS = California

SALARY = 25000

ID = 2

NAME = Allen

ADDRESS = Texas

SALARY = 15000

ID = 3

NAME = Teddy

ADDRESS = Norway

SALARY = 20000

ID = 4

NAME = Mark

ADDRESS = Rich-Mond

SALARY = 65000

Operation done successfully

The following Perl code shows how we can use the DELETE statement to delete any record

and then fetch and display the remaining records from our COMPANY table −

#!/usr/bin/perl

use DBI;

use strict;

my $driver = "Pg";

my $database = "testdb";

my $dsn = "DBI:$driver:dbname = $database;host = 127.0.0.1;port = 5432";

my $userid = "postgres";

my $password = "pass123";

my $dbh = DBI->connect($dsn, $userid, $password, { RaiseError => 1 })

or die $DBI::errstr;

print "Opened database successfully\n";

my $stmt = qq(DELETE from COMPANY where ID=2;);

my $rv = $dbh->do($stmt) or die $DBI::errstr;

if( $rv < 0 ) {

print $DBI::errstr;

DELETE OperationDELETE Operation

DELETE Operation

} else{

print "Total number of rows deleted : $rv\n";

}

$stmt = qq(SELECT id, name, address, salary from COMPANY;);

my $sth = $dbh->prepare( $stmt );

$rv = $sth->execute() or die $DBI::errstr;

if($rv < 0) {

print $DBI::errstr;

}

while(my @row = $sth->fetchrow_array()) {

print "ID = ". $row[0] . "\n";

print "NAME = ". $row[1] ."\n";

print "ADDRESS = ". $row[2] ."\n";

print "SALARY = ". $row[3] ."\n\n";

}

print "Operation done successfully\n";

$dbh->disconnect();

When the above given program is executed, it will produce the following result −

Opened database successfully

Total number of rows deleted : 1

ID = 1

NAME = Paul

ADDRESS = California

SALARY = 25000

ID = 3

NAME = Teddy

ADDRESS = Norway

SALARY = 20000

ID = 4

NAME = Mark

ADDRESS = Rich-Mond

SALARY = 65000

Operation done successfully

PostgreSQL - Python InterfacePostgreSQL - Python Interface

PostgreSQL - Python Interface

The PostgreSQL can be integrated with Python using psycopg2 module. sycopg2 is a

PostgreSQL database adapter for the Python programming language. psycopg2 was written

with the aim of being very small and fast, and stable as a rock. You do not need to install

this module separately because it is shipped, by default, along with Python version 2.5.x

onwards.

InstallationInstallation

Installation

If you do not have it installed on your machine then you can use yum command to install it

as follows −

$yum install python-psycopg2

To use psycopg2 module, you must first create a Connection object that represents the

database and then optionally you can create cursor object which will help you in executing

all the SQL statements.

The following are important psycopg2 module routines, which can suffice your requirement

to work with PostgreSQL database from your Python program. If you are looking for a

more sophisticated application, then you can look into Python psycopg2 module's official

documentation.

S. No. API & Description

psycopg2.connect(database="testdb", user="postgres",

password="cohondob", host="127.0.0.1", port="5432")

This API opens a connection to the PostgreSQL database. If database is

opened successfully, it returns a connection object.

connection.cursor()

This routine creates a cursor which will be used throughout of your database

programming with Python.

cursor.execute(sql [, optional parameters])

This routine executes an SQL statement. The SQL statement may be

parameterized (i.e., placeholders instead of SQL literals). The psycopg2

module supports placeholder using %s sign

For example:cursor.execute("insert into people values (%s, %s)", (who, age))

cursor.executemany(sql, seq_of_parameters)

This routine executes an SQL command against all parameter sequences or

mappings found in the sequence sql.

5cursor.callproc(procname[, parameters])

This routine executes a stored database procedure with the given name. The

sequence of parameters must contain one entry for each argument that the

Python psycopg2 module APIsPython psycopg2 module APIs

Python psycopg2 module APIs

procedure expects.

cursor.rowcount

This read-only attribute which returns the total number of database rows that

have been modified, inserted, or deleted by the last last execute*().

connection.commit()

This method commits the current transaction. If you do not call this method,

anything you did since the last call to commit() is not visible from other

database connections.

connection.rollback()

This method rolls back any changes to the database since the last call to

commit().

connection.close()

This method closes the database connection. Note that this does not

automatically call commit(). If you just close your database connection

without calling commit() first, your changes will be lost!

cursor.fetchone()

This method fetches the next row of a query result set, returning a single

sequence, or None when no more data is available.

cursor.fetchmany([size=cursor.arraysize])

This routine fetches the next set of rows of a query result, returning a list. An

empty list is returned when no more rows are available. The method tries to

fetch as many rows as indicated by the size parameter.

cursor.fetchall()

This routine fetches all (remaining) rows of a query result, returning a list. An

empty list is returned when no rows are available.

Connecting to DatabaseConnecting to Database

Connecting to Database

The following Python code shows how to connect to an existing database. If the database

does not exist, then it will be created and finally a database object will be returned.

Here, you can also supply database testdb as name and if database is successfully

opened, then it will give the following message −

Open database successfully

The following Python program will be used to create a table in previously created database

−

When the above given program is executed, it will create COMPANY table in your test.db

and it will display the following messages −

Opened database successfully

Table created successfully

The following Python program shows how we can create records in our COMPANY table

created in the above example −

#!/usr/bin/python

import psycopg2

conn = psycopg2.connect(database="testdb", user = "postgres", password = "pass123", host = "127.0

print "Opened database successfully"

#!/usr/bin/python

import psycopg2

conn = psycopg2.connect(database = "testdb", user = "postgres", password = "pass123", host = "127

print "Opened database successfully"

cur = conn.cursor()

cur.execute('''CREATE TABLE COMPANY

(ID INT PRIMARY KEY NOT NULL,

NAME TEXT NOT NULL,

AGE INT NOT NULL,

ADDRESS CHAR(50),

SALARY REAL);''')

print "Table created successfully"

conn.commit()

conn.close()

Create a TableCreate a Table

Create a Table

INSERT OperationINSERT Operation

INSERT Operation

When the above given program is executed, it will create given records in COMPANY table

and will display the following two lines −

Opened database successfully

Records created successfully

The following Python program shows how we can fetch and display records from our

COMPANY table created in the above example −

#!/usr/bin/python

import psycopg2

conn = psycopg2.connect(database = "testdb", user = "postgres", password = "pass123", host = "127

print "Opened database successfully"

cur = conn.cursor()

cur.execute("INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) \

VALUES (1, 'Paul', 32, 'California', 20000.00 )");

cur.execute("INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) \

VALUES (2, 'Allen', 25, 'Texas', 15000.00 )");

cur.execute("INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) \

VALUES (3, 'Teddy', 23, 'Norway', 20000.00 )");

cur.execute("INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) \

VALUES (4, 'Mark', 25, 'Rich-Mond ', 65000.00 )");

conn.commit()

print "Records created successfully";

conn.close()

#!/usr/bin/python

import psycopg2

conn = psycopg2.connect(database = "testdb", user = "postgres", password = "pass123", host = "127

print "Opened database successfully"

cur = conn.cursor()

cur.execute("SELECT id, name, address, salary from COMPANY")

rows = cur.fetchall()

for row in rows:

print "ID = ", row[0]

print "NAME = ", row[1]

print "ADDRESS = ", row[2]

print "SALARY = ", row[3], "\n"

print "Operation done successfully";

conn.close()

SELECT OperationSELECT Operation

SELECT Operation

When the above given program is executed, it will produce the following result −

Opened database successfully

ID = 1

NAME = Paul

ADDRESS = California

SALARY = 20000.0

ID = 2

NAME = Allen

ADDRESS = Texas

SALARY = 15000.0

ID = 3

NAME = Teddy

ADDRESS = Norway

SALARY = 20000.0

ID = 4

NAME = Mark

ADDRESS = Rich-Mond

SALARY = 65000.0

Operation done successfully

The following Python code shows how we can use the UPDATE statement to update any

record and then fetch and display updated records from our COMPANY table −

#!/usr/bin/python

import psycopg2

conn = psycopg2.connect(database = "testdb", user = "postgres", password = "pass123", host = "127

print "Opened database successfully"

cur = conn.cursor()

cur.execute("UPDATE COMPANY set SALARY = 25000.00 where ID = 1")

conn.commit()

print "Total number of rows updated :", cur.rowcount

cur.execute("SELECT id, name, address, salary from COMPANY")

rows = cur.fetchall()

for row in rows:

print "ID = ", row[0]

print "NAME = ", row[1]

UPDATE OperationUPDATE Operation

UPDATE Operation

When the above given program is executed, it will produce the following result −

Opened database successfully

Total number of rows updated : 1

ID = 1

NAME = Paul

ADDRESS = California

SALARY = 25000.0

ID = 2

NAME = Allen

ADDRESS = Texas

SALARY = 15000.0

ID = 3

NAME = Teddy

ADDRESS = Norway

SALARY = 20000.0

ID = 4

NAME = Mark

ADDRESS = Rich-Mond

SALARY = 65000.0

Operation done successfully

The following Python code shows how we can use the DELETE statement to delete any

record and then fetch and display the remaining records from our COMPANY table −

print "ADDRESS = ", row[2]

print "SALARY = ", row[3], "\n"

print "Operation done successfully";

conn.close()

#!/usr/bin/python

import psycopg2

conn = psycopg2.connect(database = "testdb", user = "postgres", password = "pass123", host = "127

print "Opened database successfully"

cur = conn.cursor()

cur.execute("DELETE from COMPANY where ID=2;")

conn.commit()

DELETE OperationDELETE Operation

DELETE Operation

Previous Page Next Page

When the above given program is executed, it will produce the following result −

Opened database successfully

Total number of rows deleted : 1

ID = 1

NAME = Paul

ADDRESS = California

SALARY = 20000.0

ID = 3

NAME = Teddy

ADDRESS = Norway

SALARY = 20000.0

ID = 4

NAME = Mark

ADDRESS = Rich-Mond

SALARY = 65000.0

Operation done successfully

print "Total number of rows deleted :", cur.rowcount

cur.execute("SELECT id, name, address, salary from COMPANY")

rows = cur.fetchall()

for row in rows:

print "ID = ", row[0]

print "NAME = ", row[1]

print "ADDRESS = ", row[2]

print "SALARY = ", row[3], "\n"

print "Operation done successfully";

conn.close()



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